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Editors: Arthur Gretton, Christian C. Robert
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Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures
; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1-9
Revealing Graph Bandits for Maximizing Local Influence
Alexandra Carpentier, Michal Valko; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:10-18
Convex Block-sparse Linear Regression with Expanders – Provably
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran Dinh, Luca Baldassarre, Volkan Cevher; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:19-27
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching
Daniel Ritchie, Andreas Stuhlmüller, Noah Goodman; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:28-37
Clamping Improves TRW and Mean Field Approximations
Adrian Weller, Justin Domke; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:38-46
Tightness of LP Relaxations for Almost Balanced Models
Adrian Weller, Mark Rowland, David Sontag; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:47-55
Control Functionals for Quasi-Monte Carlo Integration
Chris Oates, Mark Girolami; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:56-65
Probability Inequalities for Kernel Embeddings in Sampling without Replacement
Markus Schneider; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:66-74
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking
Nicolas Goix, Anne Sabourin, Stéphan Clémençon; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:75-83
A Robust-Equitable Copula Dependence Measure for Feature Selection
Yale Chang, Yi Li, Adam Ding, Jennifer Dy; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:84-92
Random Forest for the Contextual Bandit Problem
Raphaël Féraud, Robin Allesiardo, Tanguy Urvoy, Fabrice Clérot; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:93-101
Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics
Michael Herman, Tobias Gindele, Jörg Wagner, Felix Schmitt, Wolfram Burgard; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:102-110
Learning Sparse Additive Models with Interactions in High Dimensions
Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:111-120
Bipartite Correlation Clustering: Maximizing Agreements
Megasthenis Asteris, Anastasios Kyrillidis, Dimitris Papailiopoulos, Alexandros Dimakis; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:121-129
Breaking Sticks and Ambiguities with Adaptive Skip-gram
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry Vetrov; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:130-138
Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls
Kwang-Sung Jun, Kevin Jamieson, Robert Nowak, Xiaojin Zhu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:139-148
Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices
Jonathan Scarlett, Volkan Cevher; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:149-158
Maximum Likelihood for Variance Estimation in High-Dimensional Linear Models
Lee H. Dicker, Murat A. Erdogdu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:159-167
Scalable Gaussian Process Classification via Expectation Propagation
Daniel Hernandez-Lobato, Jose Miguel Hernandez-Lobato; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:168-176
Precision Matrix Estimation in High Dimensional Gaussian Graphical Models with Faster Rates
Lingxiao Wang, Xiang Ren, Quanquan Gu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:177-185
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On the Reducibility of Submodular Functions
Jincheng Mei, Hao Zhang, Bao-Liang Lu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:186-194
Accelerated Stochastic Gradient Descent for Minimizing Finite Sums
Atsushi Nitanda; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:195-203
Fast Convergence of Online Pairwise Learning Algorithms
Martin Boissier, Siwei Lyu, Yiming Ying, Ding-Xuan Zhou; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:204-212
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Computationally Efficient Bayesian Learning of Gaussian Process State Space Models
Andreas Svensson, Arno Solin, Simo Särkkä, Thomas Schön; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:213-221
Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables
Yaniv Tenzer, Gal Elidan; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:222-230
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes
Alexander G. de G. Matthews, James Hensman, Richard Turner, Zoubin Ghahramani; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:231-239
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Non-stochastic Best Arm Identification and Hyperparameter Optimization
Kevin Jamieson, Ameet Talwalkar; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:240-248
A Linearly-Convergent Stochastic L-BFGS Algorithm
Philipp Moritz, Robert Nishihara, Michael Jordan; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:249-258
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No Regret Bound for Extreme Bandits
Robert Nishihara, David Lopez-Paz, Leon Bottou; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:259-267
Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations
Anima Anandkumar, Prateek Jain, Yang Shi, U. N. Niranjan; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:268-276
Online Learning to Rank with Feedback at the Top
Sougata Chaudhuri, Ambuj Tewari Tewari; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:277-285
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Survey Propagation beyond Constraint Satisfaction Problems
Christopher Srinivasa, Siamak Ravanbakhsh, Brendan Frey; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:286-295
Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models
Balázs Csanád Csáji; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:296-304
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CRAFT: ClusteR-specific Assorted Feature selecTion
Vikas K. Garg, Cynthia Rudin, Tommi Jaakkola; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:305-313
Time-Varying Gaussian Process Bandit Optimization
Ilija Bogunovic, Jonathan Scarlett, Volkan Cevher; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:314-323
Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies
Weici Hu, Peter Frazier; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:324-332
Bayesian Markov Blanket Estimation
Dinu Kaufmann, Sonali Parbhoo, Aleksander Wieczorek, Sebastian Keller, David Adametz, Volker Roth; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:333-341
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation
Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John Fisher, Lars Hansen; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:342-350
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Unsupervised Ensemble Learning with Dependent Classifiers
Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:351-360
Multi-Level Cause-Effect Systems
Krzysztof Chalupka, Frederick Eberhardt, Pietro Perona; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:361-369
Deep Kernel Learning
Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:370-378
Nearly Optimal Classification for Semimetrics
Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:379-388
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Latent Point Process Allocation
Chris Lloyd, Tom Gunter, Michael Osborne, Stephen Roberts, Tom Nickson; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:389-397
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:398-407
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Bayesian Generalised Ensemble Markov Chain Monte Carlo
Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:408-416
A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning
Yan Li, Han Liu, Warren Powell; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:417-425
Optimal Statistical and Computational Rates for One Bit Matrix Completion
Renkun Ni, Quanquan Gu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:426-434
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PAC-Bayesian Bounds based on the Rényi Divergence
Luc Bégin, Pascal Germain, François Laviolette, Jean-Francis Roy; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:435-444
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Simple and Scalable Constrained Clustering: a Generalized Spectral Method
Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla, Gary Miller, Richard Peng; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:445-454
Geometry Aware Mappings for High Dimensional Sparse Factors
Avradeep Bhowmik, Nathan Liu, Erheng Zhong, Badri Bhaskar, Suju Rajan; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:455-463
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
Chen-Yu Lee, Patrick W. Gallagher, Zhuowen Tu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:464-472
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA
Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:473-481
Quantization based Fast Inner Product Search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, David Simcha; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:482-490
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An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:491-499
Learning Structured Low-Rank Representation via Matrix Factorization
Jie Shen, Ping Li; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:500-509
A PAC RL Algorithm for Episodic POMDPs
Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:510-518
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Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
Sujith Ravi, Qiming Diao; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:519-528
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Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models
Calvin McCarter, Seyoung Kim; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:528-537
Graph Connectivity in Noisy Sparse Subspace Clustering
Yining Wang, Yu-Xiang Wang, Aarti Singh; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:538-546
The Nonparametric Kernel Bayes Smoother
Yu Nishiyama, Amir Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:547-555
Universal Models of Multivariate Temporal Point Processes
Asela Gunawardana, Chris Meek; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:556-563
Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings
Zhitang Chen, Pascal Poupart, Yanhui Geng; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:573-581
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Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines
Muneki Yasuda; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:582-590
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Enumerating Equivalence Classes of Bayesian Networks using EC Graphs
Eunice Yuh-Jie Chen, Arthur Choi Choi, Adnan Darwiche; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:591-599
Low-Rank and Sparse Structure Pursuit via Alternating Minimization
Quanquan Gu, Zhaoran Wang Wang, Han Liu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:600-609
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NuC-MKL: A Convex Approach to Non Linear Multiple Kernel Learning
Eli Meirom, Pavel Kisilev; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:610-619
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization
Fanhua Shang, Yuanyuan Liu, James Cheng; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:620-629
Fast Dictionary Learning with a Smoothed Wasserstein Loss
Antoine Rolet, Marco Cuturi, Gabriel Peyré; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:630-638
New Resistance Distances with Global Information on Large Graphs
Canh Hao Nguyen, Hiroshi Mamitsuka; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:639-647
Batch Bayesian Optimization via Local Penalization
Javier Gonzalez, Zhenwen Dai, Philipp Hennig, Neil Lawrence; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:648-657
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Nonparametric Budgeted Stochastic Gradient Descent
Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Phung; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:654-572
Learning Relationships between Data Obtained Independently
Alexandra Carpentier, Teresa Schlueter; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:658-666
Fast and Scalable Structural SVM with Slack Rescaling
Heejin Choi, Ofer Meshi, Nathan Srebro; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:667-675
Probabilistic Approximate Least-Squares
Simon Bartels, Philipp Hennig; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:676-684
Approximate Inference Using DC Programming For Collective Graphical Models
Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:685-693
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Sequential Inference for Deep Gaussian Process
Yali Wang, Marcus Brubaker, Brahim Chaib-Draa, Raquel Urtasun; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:694-703
Variational Tempering
Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David Blei; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:704-712
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System
Yi Zhou, Yaoliang Yu, Wei Dai, Yingbin Liang, Eric Xing; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:713-722
Scalable MCMC for Mixed Membership Stochastic Blockmodels
Wenzhe Li, Sungjin Ahn, Max Welling; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:723-731
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Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:732-740
A Deep Generative Deconvolutional Image Model
Yunchen Pu, Win Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:741-750
Distributed Multi-Task Learning
Jialei Wang, Mladen Kolar, Nathan Srerbo; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:751-760
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models
Rishit Sheth, Roni Khardon; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:761-769
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation
Sebastian Tschiatschek, Josip Djolonga, Andreas Krause; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:770-779
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm
Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:780-789
GLASSES: Relieving The Myopia Of Bayesian Optimisation
Javier Gonzalez, Michael Osborne, Neil Lawrence; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:790-799
Stochastic Variational Inference for the HDP-HMM
Aonan Zhang, San Gultekin, John Paisley; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:800-808
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Stochastic Neural Networks with Monotonic Activation Functions
Siamak Ravanbakhsh, Barnabas Poczos, Jeff Schneider, Dale Schuurmans, Russell Greiner; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:809-818
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(Bandit) Convex Optimization with Biased Noisy Gradient Oracles
Xiaowei Hu, Prashanth L.A., András György, Csaba Szepesvari; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:819-828
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Variational Gaussian Copula Inference
Shaobo Han, Xuejun Liao, David Dunson, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:829-838
Low-Rank Approximation of Weighted Tree Automata
Guillaume Rabusseau, Borja Balle, Shay Cohen; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:839-847
Accelerating Online Convex Optimization via Adaptive Prediction
Mehryar Mohri, Scott Yang; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:848-856
Scalable geometric density estimation
Ye Wang, Antonio Canale, David Dunson; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:857-865
Model-based Co-clustering for High Dimensional Sparse Data
Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:866-874
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections
Christina Heinze, Brian McWilliams, Nicolai Meinshausen; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:875-883
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
Chun-Liang Li, Kirthevasan Kandasamy, Barnabas Poczos, Jeff Schneider; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:884-892
On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games
Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:893-901
Semi-Supervised Learning with Adaptive Spectral Transform
Hanxiao Liu, Yiming Yang; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:902-910
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Pseudo-Marginal Slice Sampling
Iain Murray, Matthew Graham; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:911-919
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How to Learn a Graph from Smooth Signals
Vassilis Kalofolias; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:920-929
Ordered Weighted L1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects
Mario Figueiredo, Robert Nowak; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:930-938
Pareto Front Identification from Stochastic Bandit Feedback
Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina Drugan; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:939-947
Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces
Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:948-956
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AdaDelay: Delay Adaptive Distributed Stochastic Optimization
Suvrit Sra, Adams Wei Yu, Mu Li, Alex Smola; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:957-965
Exponential Stochastic Cellular Automata for Massively Parallel Inference
Manzil Zaheer, Michael Wick, Jean-Baptiste Tristan, Alex Smola, Guy Steele; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:966-975
Globally Sparse Probabilistic PCA
Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:976-984
Provable Bayesian Inference via Particle Mirror Descent
Bo Dai, Niao He, Hanjun Dai, Le Song; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:985-994
Unsupervised Feature Selection by Preserving Stochastic Neighbors
Xiaokai Wei, Philip S. Yu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:995-1003
Improved Learning Complexity in Combinatorial Pure Exploration Bandits
Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter Bartlett; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1004-1012
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
William Herlands, Andrew Wilson, Hannes Nickisch, Seth Flaxman, Daniel Neill, Wilbert Van Panhuis, Eric Xing; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1013-1021
Optimization as Estimation with Gaussian Processes in Bandit Settings
Zi Wang, Bolei Zhou, Stefanie Jegelka; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1022-1031
A Convex Surrogate Operator for General Non-Modular Loss Functions
Jiaqian Yu, Matthew Blaschko; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1032-1041
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Inference for High-dimensional Exponential Family Graphical Models
Jialei Wang, Mladen Kolar; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1042-1050
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Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization
Changyou Chen, David Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1051-1060
Fitting Spectral Decay with the k-Support Norm
Andrew McDonald, Massimiliano Pontil, Dimitris Stamos; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1061-1069
Early Stopping as Nonparametric Variational Inference
David Duvenaud, Dougal Maclaurin, Ryan Adams; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1070-1077
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Bayesian Nonparametric Kernel-Learning
Junier B. Oliva, Avinava Dubey, Andrew G. Wilson, Barnabas Poczos, Jeff Schneider, Eric P. Xing; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1078-1086
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Tight Variational Bounds via Random Projections and I-Projections
Lun-Kai Hsu, Tudor Achim, Stefano Ermon; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1087-1095
Bethe Learning of Graphical Models via MAP Decoding
Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1096-1104
Determinantal Regularization for Ensemble Variable Selection
Veronika Rockova, Gemma Moran, Edward George; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1105-1113
Scalable and Sound Low-Rank Tensor Learning
Hao Cheng, Yaoliang Yu, Xinhua Zhang, Eric Xing, Dale Schuurmans; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1114-1123
Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information
Changwei Hu, Piyush Rai, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1124-1132
Topic-Based Embeddings for Learning from Large Knowledge Graphs
Changwei Hu, Piyush Rai, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1133-1141
Consistently Estimating Markov Chains with Noisy Aggregate Data
Garrett Bernstein, Daniel Sheldon; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1142-1150
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction
Tom Goldstein, Gavin Taylor, Kawika Barabin, Kent Sayre; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1151-1158
Improper Deep Kernels
Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1159-1167
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Unbounded Bayesian Optimization via Regularization
Bobak Shahriari, Alexandre Bouchard-Cote, Nando Freitas; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1168-1176
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Non-Gaussian Component Analysis with Log-Density Gradient Estimation
Hiroaki Sasaki, Gang Niu, Masashi Sugiyama; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1177-1185
Online Learning with Noisy Side Observations
Tomáš Kocák, Gergely Neu, Michal Valko; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1186-1194
Black-Box Policy Search with Probabilistic Programs
Jan-Willem Vandemeent, Brooks Paige, David Tolpin, Frank Wood; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1195-1204
Efficient Bregman Projections onto the Permutahedron and Related Polytopes
Cong Han Lim, Stephen J. Wright; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1205-1213
On Searching for Generalized Instrumental Variables
Benito Zander, Maciej Liśkiewicz; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1214-1222
Provable Tensor Methods for Learning Mixtures of Generalized Linear Models
Hanie Sedghi, Majid Janzamin, Anima Anandkumar; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1223-1231
Controlling Bias in Adaptive Data Analysis Using Information Theory
Daniel Russo, James Zou; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1232-1240
A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees
Jean-Francis Roy, Mario Marchand, François Laviolette; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1241-1249
Graph Sparsification Approaches for Laplacian Smoothing
Veeru Sadhanala, Yu-Xiang Wang, Ryan Tibshirani; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1250-1259
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation
Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1260-1269
Robust Covariate Shift Regression
Xiangli Chen, Mathew Monfort, Anqi Liu, Brian D. Ziebart; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1270-1279
On Lloyd’s Algorithm: New Theoretical Insights for Clustering in Practice
Cheng Tang, Claire Monteleoni; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1280-1289
Towards Stability and Optimality in Stochastic Gradient Descent
Panos Toulis, Dustin Tran, Edo Airoldi; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1290-1298
Communication Efficient Distributed Agnostic Boosting
Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1299-1307
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Private Causal Inference
Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1308-1317
Parallel Markov Chain Monte Carlo via Spectral Clustering
Guillaume Basse, Aaron Smith, Natesh Pillai; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1318-1327
Efficient Sampling for k-Determinantal Point Processes
Chengtao Li, Stefanie Jegelka, Suvrit Sra; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1328-1337
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A Fast and Reliable Policy Improvement Algorithm
Yasin Abbasi-Yadkori, Peter L. Bartlett, Stephen J. Wright; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1338-1346
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization
Zhao Song, Ricardo Henao, David Carlson, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1347-1355
Active Learning Algorithms for Graphical Model Selection
Gautamd Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong H. Park; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1356-1364
Streaming Kernel Principal Component Analysis
Mina Ghashami, Daniel J. Perry, Jeff Phillips; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1365-1374
Back to the Future: Radial Basis Function Networks Revisited
Qichao Que, Mikhail Belkin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1375-1383
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions
Loic Landrieu, Guillaume Obozinski; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1384-1393
Loss Bounds and Time Complexity for Speed Priors
Daniel Filan, Jan Leike, Marcus Hutter; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1394-1402
NYTRO: When Subsampling Meets Early Stopping
Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1403-1411
Randomization and The Pernicious Effects of Limited Budgets on Auction Experiments
Guillaume W. Basse, Hossein Azari Soufiani, Diane Lambert; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1412-1420
Spectral M-estimation with Applications to Hidden Markov Models
Dustin Tran, Minjae Kim, Finale Doshi-Velez; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1421-1430
Chained Gaussian Processes
Alan D. Saul, James Hensman, Aki Vehtari, Neil D. Lawrence; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1431-1440
Multiresolution Matrix Compression
Nedelina Teneva, Pramod Kaushik Mudrakarta, Risi Kondor; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1441-1449
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Supervised Neighborhoods for Distributed Nonparametric Regression
Adam Bloniarz, Ameet Talwalkar, Bin Yu, Christopher Wu; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1450-1459
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation
Dejiao Zhang, Laura Balzano; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1460-1468
Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks
Abdullah Rashwan, Han Zhao, Pascal Poupart; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1469-1477
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Mondrian Forests for Large-Scale Regression when Uncertainty Matters
Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1478-1487
Online (and Offline) Robust PCA: Novel Algorithms and Performance Guarantees
Jinchun Zhan, Brian Lois, Han Guo, Namrata Vaswani; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1488-1496
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Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization
Yan Kaganovsky, Ikenna Odinaka, David Carlson, Lawrence Carin; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1497-1505
Discriminative Structure Learning of Arithmetic Circuits
Amirmohammad Rooshenas, Daniel Lowd; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1506-1514
One Scan 1-Bit Compressed Sensing
Ping Li; Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, PMLR 51:1515-1523
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