[edit]
[edit]
Editors: Eric P. Xing, Tony Jebara
A Discriminative Latent Variable Model for Online Clustering
; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):1-9
Kernel Mean Estimation and Stein Effect
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton, Bernhard Schoelkopf; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):10-18
Demystifying Information-Theoretic Clustering
Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):19-27
Covering Number for Efficient Heuristic-based POMDP Planning
Zongzhang Zhang, David Hsu, Wee Sun Lee; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):28-36
The Coherent Loss Function for Classification
Wenzhuo Yang, Melvyn Sim, Huan Xu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):37-45
Fast Stochastic Alternating Direction Method of Multipliers
Wenliang Zhong, James Kwok; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):46-54
[abs][Download PDF]
Active Detection via Adaptive Submodularity
Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):55-63
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Shai Shalev-Shwartz, Tong Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):64-72
[abs][Download PDF]
An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization
Qihang Lin, Lin Xiao; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):73-81
Recurrent Convolutional Neural Networks for Scene Labeling
Pedro Pinheiro, Ronan Collobert; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):82-90
[abs][Download PDF]
A Statistical Perspective on Algorithmic Leveraging
Ping Ma, Michael Mahoney, Bin Yu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):91-99
[abs][Download PDF]
Thompson Sampling for Complex Online Problems
Aditya Gopalan, Shie Mannor, Yishay Mansour; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):100-108
Boosting multi-step autoregressive forecasts
Souhaib Ben Taieb, Rob Hyndman; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):109-117
A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data
Arun Rajkumar, Shivani Agarwal; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):118-126
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations
Timothy Mann, Shie Mannor; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):127-135
Latent Bandits.
Odalric-Ambrym Maillard, Shie Mannor; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):136-144
[abs][Download PDF]
Fast Allocation of Gaussian Process Experts
Trung Nguyen, Edwin Bonilla; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):145-153
[abs][Download PDF]
Von Mises-Fisher Clustering Models
Siddharth Gopal, Yiming Yang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):154-162
Convergence rates for persistence diagram estimation in Topological Data Analysis
Frédéric Chazal, Marc Glisse, Catherine Labruère, Bertrand Michel; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):163-171
[abs][Download PDF]
Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs
Fabian Gieseke, Justin Heinermann, Cosmin Oancea, Christian Igel; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):172-180
[abs][Download PDF]
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget
Anoop Korattikara, Yutian Chen, Max Welling; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):181-189
Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis
Jian Tang, Zhaoshi Meng, Xuanlong Nguyen, Qiaozhu Mei, Ming Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):190-198
[abs][Download PDF]
The Inverse Regression Topic Model
Maxim Rabinovich, David Blei; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):199-207
A Consistent Histogram Estimator for Exchangeable Graph Models
Stanley Chan, Edoardo Airoldi; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):208-216
[abs][Download PDF]
Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data
Benjamin Letham, Wei Sun, Anshul Sheopuri; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):217-225
[abs][Download PDF]
Towards Minimax Online Learning with Unknown Time Horizon
Haipeng Luo, Robert Schapire; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):226-234
Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball
Andrew Miller, Luke Bornn, Ryan Adams, Kirk Goldsberry; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):235-243
Margins, Kernels and Non-linear Smoothed Perceptrons
Aaditya Ramdas, Javier Peña; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):244-252
Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models
Shike Mei, Jun Zhu, Jerry Zhu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):253-261
[abs][Download PDF]
Learning Theory and Algorithms for revenue optimization in second price auctions with reserve
Mehryar Mohri, Andres Munoz Medina; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):262-270
Low-density Parity Constraints for Hashing-Based Discrete Integration
Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):271-279
Prediction with Limited Advice and Multiarmed Bandits with Paid Observations
Yevgeny Seldin, Peter Bartlett, Koby Crammer, Yasin Abbasi-Yadkori; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):280-287
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts
Tien Vu Nguyen, Dinh Phung, Xuanlong Nguyen, Swetha Venkatesh, Hung Bui; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):288-296
Large-Margin Metric Learning for Constrained Partitioning Problems
Rémi Lajugie, Francis Bach, Sylvain Arlot; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):297-305
[abs][Download PDF]
Wasserstein Propagation for Semi-Supervised Learning
Justin Solomon, Raif Rustamov, Leonidas Guibas, Adrian Butscher; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):306-314
[abs][Download PDF]
Max-Margin Infinite Hidden Markov Models
Aonan Zhang, Jun Zhu, Bo Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):315-323
[abs][Download PDF]
Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function
Yong Liu, Shali Jiang, Shizhong Liao; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):324-332
[abs][Download PDF]
Generalized Exponential Concentration Inequality for Renyi Divergence Estimation
Shashank Singh, Barnabas Poczos; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):333-341
[abs][Download PDF]
Boosting with Online Binary Learners for the Multiclass Bandit Problem
Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):342-350
[abs][Download PDF]
Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm
Tasuku Soma, Naonori Kakimura, Kazuhiro Inaba, Ken-ichi Kawarabayashi; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):351-359
Computing Parametric Ranking Models via Rank-Breaking
Hossein Azari Soufiani, David Parkes, Lirong Xia; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):360-368
Tracking Adversarial Targets
Yasin Abbasi-Yadkori, Peter Bartlett, Varun Kanade; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):369-377
Online Bayesian Passive-Aggressive Learning
Tianlin Shi, Jun Zhu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):378-386
Deterministic Policy Gradient Algorithms
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin Riedmiller; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):387-395
Modeling Correlated Arrival Events with Latent Semi-Markov Processes
Wenzhao Lian, Vinayak Rao, Brian Eriksson, Lawrence Carin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):396-404
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach
Rémi Bardenet, Arnaud Doucet, Chris Holmes; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):405-413
Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost
Ferdinando Cicalese, Eduardo Laber, Aline Medeiros Saettler; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):414-422
[abs][Download PDF]
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification
Chun-Liang Li, Hsuan-Tien Lin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):423-431
On Measure Concentration of Random Maximum A-Posteriori Perturbations
Francesco Orabona, Tamir Hazan, Anand Sarwate, Tommi Jaakkola; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):432-440
Bias in Natural Actor-Critic Algorithms
Philip Thomas; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):441-448
[abs][Download PDF]
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning
François Denis, Mattias Gybels, Amaury Habrard; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):449-457
[abs][Download PDF]
On Modelling Non-linear Topical Dependencies
Zhixing Li, Siqiang Wen, Juanzi Li, Peng Zhang, Jie Tang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):458-466
[abs][Download PDF]
A Deep and Tractable Density Estimator
Benigno Uria, Iain Murray, Hugo Larochelle; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):467-475
[abs][Download PDF]
(Near) Dimension Independent Risk Bounds for Differentially Private Learning
Prateek Jain, Abhradeep Guha Thakurta; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):476-484
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael Mahoney; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):485-493
Discriminative Features via Generalized Eigenvectors
Nikos Karampatziakis, Paul Mineiro; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):494-502
[abs][Download PDF]
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint
Ji Liu, Jieping Ye, Ryohei Fujimaki; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):503-511
[abs][Download PDF]
Online Learning in Markov Decision Processes with Changing Cost Sequences
Travis Dick, Andras Gyorgy, Csaba Szepesvari; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):512-520
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms
Richard Combes, Alexandre Proutiere; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):521-529
[abs][Download PDF]
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
Arun Iyer, Saketha Nath, Sunita Sarawagi; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):530-538
Asymptotically consistent estimation of the number of change points in highly dependent time series
Azadeh Khaleghi, Daniil Ryabko; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):539-547
[abs][Download PDF]
Coordinate-descent for learning orthogonal matrices through Givens rotations
Uri Shalit, Gal Chechik; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):548-556
Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search
Anshumali Shrivastava, Ping Li; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):557-565
[abs][Download PDF]
A Divide-and-Conquer Solver for Kernel Support Vector Machines
Cho-Jui Hsieh, Si Si, Inderjit Dhillon; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):566-574
Nuclear Norm Minimization via Active Subspace Selection
Cho-Jui Hsieh, Peder Olsen; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):575-583
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):584-592
[abs][Download PDF]
Large-scale Multi-label Learning with Missing Labels
Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit Dhillon; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):593-601
Learning Graphs with a Few Hubs
Rashish Tandon, Pradeep Ravikumar; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):602-610
Agnostic Bayesian Learning of Ensembles
Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):611-619
Towards an optimal stochastic alternating direction method of multipliers
Samaneh Azadi, Suvrit Sra; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):620-628
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions
Shiwei Lan, Bo Zhou, Babak Shahbaba; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):629-637
[abs][Download PDF]
Efficient Continuous-Time Markov Chain Estimation
Monir Hajiaghayi, Bonnie Kirkpatrick, Liangliang Wang, Alexandre Bouchard-Côté; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):638-646
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):647-655
[abs][Download PDF]
Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers
Dani Yogatama, Noah Smith; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):656-664
[abs][Download PDF]
Narrowing the Gap: Random Forests In Theory and In Practice
Misha Denil, David Matheson, Nando De Freitas; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):665-673
Coherent Matrix Completion
Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):674-682
Admixture of Poisson MRFs: A Topic Model with Word Dependencies
David Inouye, Pradeep Ravikumar, Inderjit Dhillon; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):683-691
True Online TD(lambda)
Harm Seijen, Rich Sutton; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):692-700
[abs][Download PDF]
Memory Efficient Kernel Approximation
Si Si, Cho-Jui Hsieh, Inderjit Dhillon; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):701-709
Learning Sum-Product Networks with Direct and Indirect Variable Interactions
Amirmohammad Rooshenas, Daniel Lowd; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):710-718
Hamiltonian Monte Carlo Without Detailed Balance
Jascha Sohl-Dickstein, Mayur Mudigonda, Michael DeWeese; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):719-726
[abs][Download PDF]
Filtering with Abstract Particles
Jacob Steinhardt, Percy Liang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):727-735
Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers
Taiji Suzuki; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):736-744
Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction
Jian Zhou, Olga Troyanskaya; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):745-753
[abs][Download PDF]
An Efficient Approach for Assessing Hyperparameter Importance
Frank Hutter, Holger Hoos, Kevin Leyton-Brown; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):754-762
An Information Geometry of Statistical Manifold Learning
Ke Sun, Stéphane Marchand-Maillet; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1-9
Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem
Masrour Zoghi, Shimon Whiteson, Remi Munos, Maarten Rijke; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):10-18
Compact Random Feature Maps
Raffay Hamid, Ying Xiao, Alex Gittens, Dennis Decoste; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):19-27
[abs][Download PDF]
Concentration in unbounded metric spaces and algorithmic stability
Aryeh Kontorovich; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):28-36
Heavy-tailed regression with a generalized median-of-means
Daniel Hsu, Sivan Sabato; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):37-45
[abs][Download PDF]
Spectral Bandits for Smooth Graph Functions
Michal Valko, Remi Munos, Branislav Kveton, Tomáš Kocák; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):46-54
Robust Principal Component Analysis with Complex Noise
Qian Zhao, Deyu Meng, Zongben Xu, Wangmeng Zuo, Lei Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):55-63
Scalable Semidefinite Relaxation for Maximum A Posterior Estimation
Qixing Huang, Yuxin Chen, Leonidas Guibas; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):64-72
Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery
Cun Mu, Bo Huang, John Wright, Donald Goldfarb; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):73-81
Automated inference of point of view from user interactions in collective intelligence venues
Sanmay Das, Allen Lavoie; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):82-90
[abs][Download PDF]
Rank-One Matrix Pursuit for Matrix Completion
Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):91-99
[abs][Download PDF]
Near-Optimal Joint Object Matching via Convex Relaxation
Yuxin Chen, Leonidas Guibas, Qixing Huang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):100-108
Convex Total Least Squares
Dmitry Malioutov, Nikolai Slavov; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):109-117
[abs][Download PDF]
On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection
Pratik Jawanpuria, Manik Varma, Saketha Nath; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):118-126
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization
Xiaotong Yuan, Ping Li, Tong Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):127-135
[abs][Download PDF]
A Unified Framework for Consistency of Regularized Loss Minimizers
Jean Honorio, Tommi Jaakkola; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):136-144
Geodesic Distance Function Learning via Heat Flow on Vector Fields
Binbin Lin, Ji Yang, Xiaofei He, Jieping Ye; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):145-153
[abs][Download PDF]
Near-Optimally Teaching the Crowd to Classify
Adish Singla, Ilija Bogunovic, Gabor Bartok, Amin Karbasi, Andreas Krause; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):154-162
On the convergence of no-regret learning in selfish routing
Walid Krichene, Benjamin Drighès, Alexandre Bayen; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):163-171
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques
Jérémie Mary, Philippe Preux, Olivier Nicol; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):172-180
Scaling Up Robust MDPs using Function Approximation
Aviv Tamar, Shie Mannor, Huan Xu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):181-189
Marginal Structured SVM with Hidden Variables
Wei Ping, Qiang Liu, Alex Ihler; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):190-198
Linear and Parallel Learning of Markov Random Fields
Yariv Mizrahi, Misha Denil, Nando De Freitas; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):199-207
[abs][Download PDF]
Pitfalls in the use of Parallel Inference for the Dirichlet Process
Yarin Gal, Zoubin Ghahramani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):208-216
[abs][Download PDF]
Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing
Yuan Zhou, Xi Chen, Jian Li; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):217-225
Deep Generative Stochastic Networks Trainable by Backprop
Yoshua Bengio, Eric Laufer, Guillaume Alain, Jason Yosinski; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):226-234
A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models
Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, Jieping Ye; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):235-243
Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting
Yudong Chen, Jiaming Xu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):244-252
Gaussian Process Optimization with Mutual Information
Emile Contal, Vianney Perchet, Nicolas Vayatis; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):253-261
[abs][Download PDF]
Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy
Dengyong Zhou, Qiang Liu, John Platt, Christopher Meek; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):262-270
[abs][Download PDF]
Exchangeable Variable Models
Mathias Niepert, Pedro Domingos; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):271-279
Clustering in the Presence of Background Noise
Shai Ben-David, Nika Haghtalab; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):280-288
Safe Screening with Variational Inequalities and Its Application to Lasso
Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):289-297
Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks
Shan-Hung Wu, Hao-Heng Chien, Kuan-Hua Lin, Philip Yu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):298-306
Signal recovery from Pooling Representations
Joan Bruna Estrach, Arthur Szlam, Yann LeCun; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):307-315
PAC-inspired Option Discovery in Lifelong Reinforcement Learning
Emma Brunskill, Lihong Li; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):316-324
Multi-label Classification via Feature-aware Implicit Label Space Encoding
Zijia Lin, Guiguang Ding, Mingqing Hu, Jianmin Wang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):325-333
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications
Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):334-342
Anomaly Ranking as Supervised Bipartite Ranking
Stephan Clémençon, Sylvain Robbiano; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):343-351
[abs][Download PDF]
Hierarchical Quasi-Clustering Methods for Asymmetric Networks
Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro, Santiago Segarra; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):352-360
Rectangular Tiling Process
Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada, Naonori Ueda; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):361-369
Two-Stage Metric Learning
Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):370-378
Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices
Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):379-387
Elementary Estimators for High-Dimensional Linear Regression
Eunho Yang, Aurelie Lozano, Pradeep Ravikumar; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):388-396
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments
Eunho Yang, Aurelie Lozano, Pradeep Ravikumar; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):397-405
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically
Yuan Fang, Kevin Chang, Hady Lauw; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):406-414
Bayesian Max-margin Multi-Task Learning with Data Augmentation
Chengtao Li, Jun Zhu, Jianfei Chen; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):415-423
[abs][Download PDF]
Sparse Reinforcement Learning via Convex Optimization
Zhiwei Qin, Weichang Li, Firdaus Janoos; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):424-432
Gaussian Process Classification and Active Learning with Multiple Annotators
Filipe Rodrigues, Francisco Pereira, Bernardete Ribeiro; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):433-441
Structured Prediction of Network Response
Hongyu Su, Aristides Gionis, Juho Rousu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):442-450
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
Gavin Taylor, Connor Geer, David Piekut; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):451-459
[abs][Download PDF]
Optimization Equivalence of Divergences Improves Neighbor Embedding
Zhirong Yang, Jaakko Peltonen, Samuel Kaski; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):460-468
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm
Ji Liu, Steve Wright, Christopher Re, Victor Bittorf, Srikrishna Sridhar; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):469-477
[abs][Download PDF]
Consistency of Causal Inference under the Additive Noise Model
Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schölkopf; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):478-486
[abs][Download PDF]
Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm
Alexander Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):487-495
[abs][Download PDF]
Linear Programming for Large-Scale Markov Decision Problems
Alan Malek, Yasin Abbasi-Yadkori, Peter Bartlett; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):496-504
Linear Time Solver for Primal SVM
Feiping Nie, Yizhen Huang, Heng Huang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):505-513
[abs][Download PDF]
Memory (and Time) Efficient Sequential Monte Carlo
Seong-Hwan Jun, Alexandre Bouchard-Côté; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):514-522
Scaling SVM and Least Absolute Deviations via Exact Data Reduction
Jie Wang, Peter Wonka, Jieping Ye; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):523-531
Latent Semantic Representation Learning for Scene Classification
Xin Li, Yuhong Guo; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):532-540
[abs][Download PDF]
Least Squares Revisited: Scalable Approaches for Multi-class Prediction
Alekh Agarwal, Sham Kakade, Nikos Karampatziakis, Le Song, Gregory Valiant; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):541-549
[abs][Download PDF]
Local algorithms for interactive clustering
Pranjal Awasthi, Maria Balcan, Konstantin Voevodski; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):550-558
[abs][Download PDF]
Model-Based Relational RL When Object Existence is Partially Observable
Ngo Ahn Vien, Marc Toussaint; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):559-567
[abs][Download PDF]
A new Q(lambda) with interim forward view and Monte Carlo equivalence
Rich Sutton, Ashique Rupam Mahmood, Doina Precup, Hado Hasselt; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):568-576
On Robustness and Regularization of Structural Support Vector Machines
Mohamad Ali Torkamani, Daniel Lowd; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):577-585
Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting
Oscar Beijbom, Mohammad Saberian, David Kriegman, Nuno Vasconcelos; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):586-594
Multimodal Neural Language Models
Ryan Kiros, Ruslan Salakhutdinov, Rich Zemel; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):595-603
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods
Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):604-612
[abs][Download PDF]
Alternating Minimization for Mixed Linear Regression
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):613-621
Stochastic Neighbor Compression
Matt Kusner, Stephen Tyree, Kilian Weinberger, Kunal Agrawal; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):622-630
[abs][Download PDF]
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification
Junfeng Wen, Chun-Nam Yu, Russell Greiner; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):631-639
Nonparametric Estimation of Multi-View Latent Variable Models
Le Song, Animashree Anandkumar, Bo Dai, Bo Xie; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):640-648
Structured Generative Models of Natural Source Code
Chris Maddison, Daniel Tarlow; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):649-657
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data
Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):658-666
Statistical analysis of stochastic gradient methods for generalized linear models
Panagiotis Toulis, Edoardo Airoldi, Jason Rennie; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):667-675
[abs][Download PDF]
Coding for Random Projections
Ping Li, Michael Mitzenmacher, Anshumali Shrivastava; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):676-684
[abs][Download PDF]
Fast Computation of Wasserstein Barycenters
Marco Cuturi, Arnaud Doucet; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):685-693
[abs][Download PDF]
Global graph kernels using geometric embeddings
Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Chiranjib Bhattacharyya; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):694-702
Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data
Zhiyuan Chen, Bing Liu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):703-711
K-means recovers ICA filters when independent components are sparse
Alon Vinnikov, Shai Shalev-Shwartz; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):712-720
Learning Mixtures of Linear Classifiers
Yuekai Sun, Stratis Ioannidis, Andrea Montanari; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):721-729
The Falling Factorial Basis and Its Statistical Applications
Yu-Xiang Wang, Alex Smola, Ryan Tibshirani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):730-738
Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes
Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet, Mohan Kankanhalli; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):739-747
A Unifying View of Representer Theorems
Andreas Argyriou, Francesco Dinuzzo; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):748-756
Online Clustering of Bandits
Claudio Gentile, Shuai Li, Giovanni Zappella; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):757-765
Cold-start Active Learning with Robust Ordinal Matrix Factorization
Neil Houlsby, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):766-774
Multivariate Maximal Correlation Analysis
Hoang Vu Nguyen, Emmanuel Müller, Jilles Vreeken, Pavel Efros, Klemens Böhm; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):775-783
[abs][Download PDF]
Efficient Label Propagation
Yasuhiro Fujiwara, Go Irie; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):784-792
[abs][Download PDF]
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm
Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schoelkopf; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):793-801
Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising
Ling Yan, Wu-Jun Li, Gui-Rong Xue, Dingyi Han; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):802-810
[abs][Download PDF]
Putting MRFs on a Tensor Train
Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry Vetrov; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):811-819
Efficient Algorithms for Robust One-bit Compressive Sensing
Lijun Zhang, Jinfeng Yi, Rong Jin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):820-828
Learning Complex Neural Network Policies with Trajectory Optimization
Sergey Levine, Vladlen Koltun; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):829-837
Composite Quantization for Approximate Nearest Neighbor Search
Ting Zhang, Chao Du, Jingdong Wang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):838-846
Local Ordinal Embedding
Yoshikazu Terada, Ulrike Luxburg; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):847-855
Reducing Dueling Bandits to Cardinal Bandits
Nir Ailon, Zohar Karnin, Thorsten Joachims; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):856-864
Large-margin Weakly Supervised Dimensionality Reduction
Chang Xu, Dacheng Tao, Chao Xu, Yong Rui; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):865-873
Joint Inference of Multiple Label Types in Large Networks
Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang, Sofus Macskassy; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):874-882
[abs][Download PDF]
Hard-Margin Active Linear Regression
Elad Hazan, Zohar Karnin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):883-891
[abs][Download PDF]
Maximum Margin Multiclass Nearest Neighbors
Aryeh Kontorovich, Roi Weiss; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):892-900
Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications
Tian Lin, Bruno Abrahao, Robert Kleinberg, John Lui, Wei Chen; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):901-909
Sparse meta-Gaussian information bottleneck
Melani Rey, Volker Roth, Thomas Fuchs; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):910-918
Nonparametric Estimation of Renyi Divergence and Friends
Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):919-927
Robust Inverse Covariance Estimation under Noisy Measurements
Jun-Kun Wang, Shou-de Lin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):928-936
[abs][Download PDF]
Bayesian Optimization with Inequality Constraints
Jacob Gardner, Matt Kusner, Zhixiang, Kilian Weinberger, John Cunningham; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):937-945
Circulant Binary Embedding
Felix Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):946-954
[abs][Download PDF]
Multiple Testing under Dependence via Semiparametric Graphical Models
Jie Liu, Chunming Zhang, Elizabeth Burnside, David Page; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):955-963
Making Fisher Discriminant Analysis Scalable
Bojun Tu, Zhihua Zhang, Shusen Wang, Hui Qian; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):964-972
Hierarchical Dirichlet Scaling Process
Dongwoo Kim, Alice Oh; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):973-981
Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process
Issei Sato, Hiroshi Nakagawa; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):982-990
[abs][Download PDF]
A PAC-Bayesian bound for Lifelong Learning
Anastasia Pentina, Christoph Lampert; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):991-999
[abs][Download PDF]
Communication-Efficient Distributed Optimization using an Approximate Newton-type Method
Ohad Shamir, Nati Srebro, Tong Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1000-1008
Concept Drift Detection Through Resampling
Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1009-1017
Anti-differentiating approximation algorithms:A case study with min-cuts, spectral, and flow
David Gleich, Michael Mahoney; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1018-1025
[abs][Download PDF]
A Bayesian Wilcoxon signed-rank test based on the Dirichlet process
Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon, Fabrizio Ruggeri; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1026-1034
Min-Max Problems on Factor Graphs
Siamak Ravanbakhsh, Christopher Srinivasa, Brendan Frey, Russell Greiner; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1035-1043
Distributed Stochastic Gradient MCMC
Sungjin Ahn, Babak Shahbaba, Max Welling; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1044-1052
Nearest Neighbors Using Compact Sparse Codes
Anoop Cherian; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1053-1061
[abs][Download PDF]
Optimal Mean Robust Principal Component Analysis
Feiping Nie, Jianjun Yuan, Heng Huang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1062-1070
[abs][Download PDF]
Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows
Robert Busa-Fekete, Eyke Huellermeier, Balázs Szörényi; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1071-1079
Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations
Bilal Ahmed, Thomas Thesen, Karen Blackmon, Yijun Zhao, Orrin Devinsky, Ruben Kuzniecky, Carla Brodley; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1080-1088
[abs][Download PDF]
A Physics-Based Model Prior for Object-Oriented MDPs
Jonathan Scholz, Martin Levihn, Charles Isbell, David Wingate; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1089-1097
[abs][Download PDF]
Outlier Path: A Homotopy Algorithm for Robust SVM
Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Ichiro Takeuchi; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1098-1106
Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data
Naiyan Wang, Dit-Yan Yeung; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1107-1115
Latent Confusion Analysis by Normalized Gamma Construction
Issei Sato, Hisashi Kashima, Hiroshi Nakagawa; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1116-1124
Finito: A faster, permutable incremental gradient method for big data problems
Aaron Defazio, Justin Domke, Caetano; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1125-1133
Ensemble Methods for Structured Prediction
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1134-1142
Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance
Simone Romano, James Bailey, Vinh Nguyen, Karin Verspoor; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1143-1151
Preserving Modes and Messages via Diverse Particle Selection
Jason Pacheco, Silvia Zuffi, Michael Black, Erik Sudderth; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1152-1160
Nonlinear Information-Theoretic Compressive Measurement Design
Liming Wang, Abolfazl Razi, Miguel Rodrigues, Robert Calderbank, Lawrence Carin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1161-1169
Dual Query: Practical Private Query Release for High Dimensional Data
Marco Gaboardi, Emilio Jesus Gallego Arias, Justin Hsu, Aaron Roth, Zhiwei Steven Wu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1170-1178
[abs][Download PDF]
Deep Boosting
Corinna Cortes, Mehryar Mohri, Umar Syed; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1179-1187
Distributed Representations of Sentences and Documents
Quoc Le, Tomas Mikolov; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1188-1196
[abs][Download PDF]
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models
Robert McGibbon, Bharath Ramsundar, Mohammad Sultan, Gert Kiss, Vijay Pande; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1197-1205
[abs][Download PDF]
Online Multi-Task Learning for Policy Gradient Methods
Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, Matthew Taylor; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1206-1214
[abs][Download PDF]
Affinity Weighted Embedding
Jason Weston, Ron Weiss, Hector Yee; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1215-1223
[abs][Download PDF]
Learning the Parameters of Determinantal Point Process Kernels
Raja Hafiz Affandi, Emily Fox, Ryan Adams, Ben Taskar; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1224-1232
Discrete Chebyshev Classifiers
Elad Eban, Elad Mezuman, Amir Globerson; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1233-1241
[abs][Download PDF]
Deep AutoRegressive Networks
Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1242-1250
A Convergence Rate Analysis for LogitBoost, MART and Their Variant
Peng Sun, Tong Zhang, Jie Zhou; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1251-1259
Inferning with High Girth Graphical Models
Uri Heinemann, Amir Globerson; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1260-1268
Learning Latent Variable Gaussian Graphical Models
Zhaoshi Meng, Brian Eriksson, Al Hero; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1269-1277
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1278-1286
One Practical Algorithm for Both Stochastic and Adversarial Bandits
Yevgeny Seldin, Aleksandrs Slivkins; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1287-1295
Robust and Efficient Kernel Hyperparameter Paths with Guarantees
Joachim Giesen, Soeren Laue, Patrick Wieschollek; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1296-1304
[abs][Download PDF]
Active Transfer Learning under Model Shift
Xuezhi Wang, Tzu-Kuo Huang, Jeff Schneider; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1305-1313
Approximate Policy Iteration Schemes: A Comparison
Bruno Scherrer; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1314-1322
Stable and Efficient Representation Learning with Nonnegativity Constraints
Tsung-Han Lin, H. T. Kung; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1323-1331
[abs][Download PDF]
Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh, Jonathan How; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1332-1340
Memory and Computation Efficient PCA via Very Sparse Random Projections
Farhad Pourkamali Anaraki, Shannon Hughes; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1341-1349
Time-Regularized Interrupting Options (TRIO)
Timothy Mann, Daniel Mankowitz, Shie Mannor; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1350-1358
Randomized Nonlinear Component Analysis
David Lopez-Paz, Suvrit Sra, Alex Smola, Zoubin Ghahramani, Bernhard Schoelkopf; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1359-1367
[abs][Download PDF]
High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li, Rich Zemel; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1368-1376
Transductive Learning with Multi-class Volume Approximation
Gang Niu, Bo Dai, Christoffel Plessis, Masashi Sugiyama; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1377-1385
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison
Borja Balle, William Hamilton, Joelle Pineau; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1386-1394
Effective Bayesian Modeling of Groups of Related Count Time Series
Nicolas Chapados; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1395-1403
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process
Sergey Bartunov, Dmitry Vetrov; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1404-1412
[abs][Download PDF]
Discovering Latent Network Structure in Point Process Data
Scott Linderman, Ryan Adams; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1413-1421
A Kernel Independence Test for Random Processes
Kacper Chwialkowski, Arthur Gretton; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1422-1430
[abs][Download PDF]
Learning to Disentangle Factors of Variation with Manifold Interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1431-1439
[abs][Download PDF]
Learning Modular Structures from Network Data and Node Variables
Elham Azizi, Edoardo Airoldi, James Galagan; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1440-1448
[abs][Download PDF]
Probabilistic Partial Canonical Correlation Analysis
Yusuke Mukuta, Harada; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1449-1457
Skip Context Tree Switching
Marc Bellemare, Joel Veness, Erik Talvitie; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1458-1466
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians
Christopher Tosh, Sanjoy Dasgupta; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1467-1475
[abs][Download PDF]
Marginalized Denoising Auto-encoders for Nonlinear Representations
Minmin Chen, Kilian Weinberger, Fei Sha, Yoshua Bengio; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1476-1484
[abs][Download PDF]
Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations
David Barber, Yali Wang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1485-1493
[abs][Download PDF]
Fast Multi-stage Submodular Maximization
Kai Wei, Rishabh Iyer, Jeff Bilmes; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1494-1502
Programming by Feedback
Marc Schoenauer, Riad Akrour, Michele Sebag, Jean-Christophe Souplet; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1503-1511
[abs][Download PDF]
Probabilistic Matrix Factorization with Non-random Missing Data
Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1512-1520
Pursuit-Evasion Without Regret, with an Application to Trading
Lili Dworkin, Michael Kearns, Yuriy Nevmyvaka; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1521-1529
[abs][Download PDF]
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation
Sven Kurras, Ulrike Luxburg, Gilles Blanchard; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1530-1538
Riemannian Pursuit for Big Matrix Recovery
Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken, Sinno Jialin Pan; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1539-1547
Dynamic Programming Boosting for Discriminative Macro-Action Discovery
Leonidas Lefakis, Francois Fleuret; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1548-1556
[abs][Download PDF]
Online Stochastic Optimization under Correlated Bandit Feedback
Mohammad Gheshlaghi azar, Alessandro Lazaric, Emma Brunskill; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1557-1565
Weighted Graph Clustering with Non-Uniform Uncertainties
Yudong Chen, Shiau Hong Lim, Huan Xu; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1566-1574
GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results
Philip Thomas; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1575-1583
[abs][Download PDF]
A Bayesian Framework for Online Classifier Ensemble
Qinxun Bai, Henry Lam, Stan Sclaroff; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1584-1592
Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm
Jacob Steinhardt, Percy Liang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1593-1601
Gaussian Approximation of Collective Graphical Models
Liping Liu, Daniel Sheldon, Thomas Dietterich; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1602-1610
On learning to localize objects with minimal supervision
Hyun Oh Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1611-1619
[abs][Download PDF]
Multiresolution Matrix Factorization
Risi Kondor, Nedelina Teneva, Vikas Garg; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1620-1628
Learnability of the Superset Label Learning Problem
Liping Liu, Thomas Dietterich; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1629-1637
[abs][Download PDF]
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert Schapire; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1638-1646
[abs][Download PDF]
Structured Recurrent Temporal Restricted Boltzmann Machines
Roni Mittelman, Benjamin Kuipers, Silvio Savarese, Honglak Lee; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1647-1655
[abs][Download PDF]
Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David Dunson; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1656-1664
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1665-1673
Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel, Ryan Adams; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1674-1682
[abs][Download PDF]
Stochastic Gradient Hamiltonian Monte Carlo
Tianqi Chen, Emily Fox, Carlos Guestrin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1683-1691
A Deep Semi-NMF Model for Learning Hidden Representations
George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou, Bjoern Schuller; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1692-1700
Asynchronous Distributed ADMM for Consensus Optimization
Ruiliang Zhang, James Kwok; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1701-1709
[abs][Download PDF]
Spectral Regularization for Max-Margin Sequence Tagging
Ariadna Quattoni, Borja Balle, Xavier Carreras, Amir Globerson; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1710-1718
[abs][Download PDF]
Learning by Stretching Deep Networks
Gaurav Pandey, Ambedkar Dukkipati; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1719-1727
Nonnegative Sparse PCA with Provable Guarantees
Megasthenis Asteris, Dimitris Papailiopoulos, Alexandros Dimakis; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1728-1736
Active Learning of Parameterized Skills
Bruno Da Silva, George Konidaris, Andrew Barto; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1737-1745
Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael Gelbart, Ryan Adams; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1746-1754
Learning the Irreducible Representations of Commutative Lie Groups
Taco Cohen, Max Welling; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1755-1763
Towards End-To-End Speech Recognition with Recurrent Neural Networks
Alex Graves, Navdeep Jaitly; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1764-1772
[abs][Download PDF]
Multi-period Trading Prediction Markets with Connections to Machine Learning
Jinli Hu, Amos Storkey; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1773-1781
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets
Diederik Kingma, Max Welling; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1782-1790
[abs][Download PDF]
Neural Variational Inference and Learning in Belief Networks
Andriy Mnih, Karol Gregor; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1791-1799
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson, Lawrence Carin; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1800-1808
Beta Diffusion Trees
Creighton Heaukulani, David Knowles, Zoubin Ghahramani; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1809-1817
[abs][Download PDF]
Learning Character-level Representations for Part-of-Speech Tagging
Cicero Dos Santos, Bianca Zadrozny; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1818-1826
[abs][Download PDF]
Saddle Points and Accelerated Perceptron Algorithms
Adams Wei Yu, Fatma Kilinc-Karzan, Jaime Carbonell; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1827-1835
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization
Hua Wang, Feiping Nie, Heng Huang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1836-1844
[abs][Download PDF]
Learning from Contagion (Without Timestamps)
Kareem Amin, Hoda Heidari, Michael Kearns; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1845-1853
Stochastic Variational Inference for Bayesian Time Series Models
Matthew Johnson, Alan Willsky; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1854-1862
[abs][Download PDF]
A Clockwork RNN
Jan Koutnik, Klaus Greff, Faustino Gomez, Juergen Schmidhuber; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1863-1871
[abs][Download PDF]
Estimating Latent-Variable Graphical Models using Moments and Likelihoods
Arun Tejasvi Chaganty, Percy Liang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1872-1880
Universal Matrix Completion
Srinadh Bhojanapalli, Prateek Jain; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1881-1889
Finding Dense Subgraphs via Low-Rank Bilinear Optimization
Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis, Constantine Caramanis; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1890-1898
Compositional Morphology for Word Representations and Language Modelling
Jan Botha, Phil Blunsom; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1899-1907
[abs][Download PDF]
Learning Polynomials with Neural Networks
Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1908-1916
[abs][Download PDF]
Exponential Family Matrix Completion under Structural Constraints
Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1917-1925
Sample-based approximate regularization
Philip Bachman, Amir-Massoud Farahmand, Doina Precup; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1926-1934
A Compilation Target for Probabilistic Programming Languages
Brooks Paige, Frank Wood; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1935-1943
[abs][Download PDF]
Adaptive Monte Carlo via Bandit Allocation
James Neufeld, Andras Gyorgy, Csaba Szepesvari, Dale Schuurmans; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1944-1952
Efficient Dimensionality Reduction for High-Dimensional Network Estimation
Safiye Celik, Benjamin Logsdon, Su-In Lee; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1953-1961
[abs][Download PDF]
Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes
E. Busra Celikkaya, Christian Shelton; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1962-1970
[abs][Download PDF]
Doubly Stochastic Variational Bayes for non-Conjugate Inference
Michalis Titsias, Miguel Lázaro-Gredilla; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1971-1979
Efficient Learning of Mahalanobis Metrics for Ranking
Daryl Lim, Gert Lanckriet; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1980-1988
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare
Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1989-1997
A reversible infinite HMM using normalised random measures
David Knowles, Zoubin Ghahramani, Konstantina Palla; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1998-2006
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing
Benjamin Haeffele, Eric Young, Rene Vidal; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):2007-2015
Influence Function Learning in Information Diffusion Networks
Nan Du, Yingyu Liang, Maria Balcan, Le Song; Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):2016-2024
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。