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Editors: Sanjoy Dasgupta, David McAllester
An Optimal Policy for Target Localization with Application to Electron Microscopy
; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):1-9
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Domain Generalization via Invariant Feature Representation
Krikamol Muandet, David Balduzzi, Bernhard Schölkopf; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):10-18
A Spectral Learning Approach to Range-Only SLAM
Byron Boots, Geoff Gordon; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):19-26
Near-Optimal Bounds for Cross-Validation via Loss Stability
Ravi Kumar, Daniel Lokshtanov, Sergei Vassilvitskii, Andrea Vattani; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):27-35
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Sparsity-Based Generalization Bounds for Predictive Sparse Coding
Nishant Mehta, Alexander Gray; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):36-44
Sparse Uncorrelated Linear Discriminant Analysis
Xiaowei Zhang, Delin Chu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):45-52
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Block-Coordinate Frank-Wolfe Optimization for Structural SVMs
Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):53-61
Fast Probabilistic Optimization from Noisy Gradients
Philipp Hennig; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):62-70
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Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir, Tong Zhang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):71-79
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Stochastic Alternating Direction Method of Multipliers
Hua Ouyang, Niao He, Long Tran, Alexander Gray; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):80-88
Noisy Sparse Subspace Clustering
Yu-Xiang Wang, Huan Xu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):89-97
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models
Sinead Williamson, Avinava Dubey, Eric Xing; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):98-106
Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction
Sébastien Giguère, François Laviolette, Mario Marchand, Khadidja Sylla; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):107-114
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
James Bergstra, Daniel Yamins, David Cox; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):115-123
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Gibbs Max-Margin Topic Models with Fast Sampling Algorithms
Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):124-132
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Cost-Sensitive Tree of Classifiers
Zhixiang Xu, Matt Kusner, Kilian Weinberger, Minmin Chen; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):133-141
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Learning Hash Functions Using Column Generation
Xi Li, Guosheng Lin, Chunhua Shen, Anton Hengel, Anthony Dick; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):142-150
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Combinatorial Multi-Armed Bandit: General Framework and Applications
Wei Chen, Yajun Wang, Yang Yuan; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):151-159
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization
Yuxin Chen, Andreas Krause; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):160-168
Convex formulations of radius-margin based Support Vector Machines
Huyen Do, Alexandros Kalousis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):169-177
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Modelling Sparse Dynamical Systems with Compressed Predictive State Representations
William L. Hamilton, Mahdi Milani Fard, Joelle Pineau; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):178-186
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A Machine Learning Framework for Programming by Example
Aditya Menon, Omer Tamuz, Sumit Gulwani, Butler Lampson, Adam Kalai; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):187-195
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Discriminatively Activated Sparselets
Ross Girshick, Hyun Oh Song, Trevor Darrell; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):196-204
The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification
Ofir Pele, Ben Taskar, Amir Globerson, Michael Werman; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):205-213
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Fixed-Point Model For Structured Labeling
Quannan Li, Jingdong Wang, David Wipf, Zhuowen Tu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):214-221
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Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation
Boqing Gong, Kristen Grauman, Fei Sha; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):222-230
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization
Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):231-239
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Principal Component Analysis on non-Gaussian Dependent Data
Fang Han, Han Liu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):240-248
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Learning Linear Bayesian Networks with Latent Variables
Animashree Anandkumar, Daniel Hsu, Adel Javanmard, Sham Kakade; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):249-257
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Multiple Identifications in Multi-Armed Bandits
Séebastian Bubeck, Tengyao Wang, Nitin Viswanathan; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):258-265
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Learning Optimally Sparse Support Vector Machines
Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):266-274
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks
Creighton Heaukulani, Zoubin Ghahramani; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):275-283
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Efficient Sparse Group Feature Selection via Nonconvex Optimization
Shuo Xiang, Xiaoshen Tong, Jieping Ye; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):284-292
Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation Model
Min Xiao, Yuhong Guo; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):293-301
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Maximum Variance Correction with Application to A* Search
Wenlin Chen, Kilian Weinberger, Yixin Chen; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):302-310
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Adaptive Sparsity in Gaussian Graphical Models
Eleanor Wong, Suyash Awate, P. Thomas Fletcher; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):311-319
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Average Reward Optimization Objective In Partially Observable Domains
Yuri Grinberg, Doina Precup; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):320-328
Feature Selection in High-Dimensional Classification
Mladen Kolar, Han Liu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):329-337
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Efficient Dimensionality Reduction for Canonical Correlation Analysis
Haim Avron, Christos Boutsidis, Sivan Toledo, Anastasios Zouzias; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):347-355
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Parsing epileptic events using a Markov switching process model for correlated time series
Drausin Wulsin, Emily Fox, Brian Litt; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):356-364
Optimal rates for stochastic convex optimization under Tsybakov noise condition
Aaditya Ramdas, Aarti Singh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):365-373
A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning
Arash Afkanpour, András György, Csaba Szepesvari, Michael Bowling; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):374-382
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Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery
Yudong Chen, Constantine Caramanis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):383-391
Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier Method
Taiji Suzuki; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):392-400
A New Frontier of Kernel Design for Structured Data
Kilho Shin; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):401-409
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Learning with Marginalized Corrupted Features
Laurens Maaten, Minmin Chen, Stephen Tyree, Kilian Weinberger; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):410-418
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Approximation properties of DBNs with binary hidden units and real-valued visible units
Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):419-426
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Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization
Martin Jaggi; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):427-435
General Functional Matrix Factorization Using Gradient Boosting
Tianqi Chen, Hang Li, Qiang Yang, Yong Yu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):436-444
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Iterative Learning and Denoising in Convolutional Neural Associative Memories
Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):445-453
Scaling Multidimensional Gaussian Processes using Projected Additive Approximations
Elad Gilboa, Yunus Saatçi, John Cunningham, Elad Gilboa; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):454-461
Active Learning for Multi-Objective Optimization
Marcela Zuluaga, Guillaume Sergent, Andreas Krause, Markus Püschel; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):462-470
A Generalized Kernel Approach to Structured Output Learning
Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):471-479
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Efficient Active Learning of Halfspaces: an Aggressive Approach
Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):480-488
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Enhanced statistical rankings via targeted data collection
Braxton Osting, Christoph Brune, Stanley Osher; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):489-497
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Online Feature Selection for Model-based Reinforcement Learning
Trung Nguyen, Zhuoru Li, Tomi Silander, Tze Yun Leong; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):498-506
ELLA: An Efficient Lifelong Learning Algorithm
Paul Ruvolo, Eric Eaton; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):507-515
A Structural SVM Based Approach for Optimizing Partial AUC
Harikrishna Narasimhan, Shivani Agarwal; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):516-524
Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs
K. S. Sesh Kumar, Francis Bach; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):525-533
Adaptive Task Assignment for Crowdsourced Classification
Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):534-542
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Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning
Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):543-551
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Better Mixing via Deep Representations
Yoshua Bengio, Gregoire Mesnil, Yann Dauphin, Salah Rifai; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):552-560
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Online Latent Dirichlet Allocation with Infinite Vocabulary
Ke Zhai, Jordan Boyd-Graber; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):561-569
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Characterizing the Representer Theorem
Yaoliang Yu, Hao Cheng, Dale Schuurmans, Csaba Szepesvari; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):570-578
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Dynamical Models and tracking regret in online convex programming
Eric Hall, Rebecca Willett; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):579-587
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Large-Scale Bandit Problems and KWIK Learning
Jacob Abernethy, Kareem Amin, Michael Kearns, Moez Draief; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):588-596
Vanishing Component Analysis
Roi Livni, David Lehavi, Sagi Schein, Hila Nachliely, Shai Shalev-Shwartz, Amir Globerson; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):597-605
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Learning an Internal Dynamics Model from Control Demonstration
Matthew Golub, Steven Chase, Byron Yu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):606-614
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Robust Structural Metric Learning
Daryl Lim, Gert Lanckriet, Brian McFee; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):615-623
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Constrained fractional set programs and their application in local clustering and community detection
Thomas Bühler, Shyam Sundar Rangapuram, Simon Setzer, Matthias Hein; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):624-632
Efficient Semi-supervised and Active Learning of Disjunctions
Nina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):633-641
Convex Adversarial Collective Classification
MohamadAli Torkamani, Daniel Lowd; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):642-650
Rounding Methods for Discrete Linear Classification
Yann Chevaleyre, Frédéerick Koriche, Jean-daniel Zucker; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):651-659
Mixture of Mutually Exciting Processes for Viral Diffusion
Shuang-Hong Yang, Hongyuan Zha; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):1-9
Gaussian Process Vine Copulas for Multivariate Dependence
David Lopez-Paz, Jose Miguel Hernández-Lobato, Ghahramani Zoubin; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):10-18
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Stochastic Simultaneous Optimistic Optimization
Michal Valko, Alexandra Carpentier, Rémi Munos; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):19-27
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Toward Optimal Stratification for Stratified Monte-Carlo Integration
Alexandra Carpentier, Rémi Munos; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):28-36
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A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, Jieping Ye; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):37-45
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Thurstonian Boltzmann Machines: Learning from Multiple Inequalities
Truyen Tran, Dinh Phung, Svetha Venkatesh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):46-54
A Variational Approximation for Topic Modeling of Hierarchical Corpora
Do-kyum Kim, Geoffrey Voelker, Lawrence Saul; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):55-63
Ellipsoidal Multiple Instance Learning
Gabriel Krummenacher, Cheng Soon Ong, Joachim Buhmann; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):73-81
Local Low-Rank Matrix Approximation
Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):82-90
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Generic Exploration and K-armed Voting Bandits
Tanguy Urvoy, Fabrice Clerot, Raphael Féraud, Sami Naamane; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):91-99
A unifying framework for vector-valued manifold regularization and multi-view learning
Minh Hà Quang, Loris Bazzani, Vittorio Murino; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):100-108
Learning Connections in Financial Time Series
Gartheeban Ganeshapillai, John Guttag, Andrew Lo; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):109-117
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Fast dropout training
Sida Wang, Christopher Manning; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):118-126
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Scalable Optimization of Neighbor Embedding for Visualization
Zhirong Yang, Jaakko Peltonen, Samuel Kaski; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):127-135
Precision-recall space to correct external indices for biclustering
Blaise Hanczar, Mohamed Nadif; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):136-144
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Monochromatic Bi-Clustering
Sharon Wulff, Ruth Urner, Shai Ben-David; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):145-153
Gated Autoencoders with Tied Input Weights
Droniou Alain, Sigaud Olivier; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):154-162
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Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings
Nicola Rebagliati; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):163-171
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Transition Matrix Estimation in High Dimensional Time Series
Fang Han, Han Liu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):172-180
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Label Partitioning For Sublinear Ranking
Jason Weston, Ameesh Makadia, Hector Yee; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):181-189
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Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing
Huayan Wang, Koller Daphne; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):190-198
Collaborative hyperparameter tuning
Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):199-207
SADA: A General Framework to Support Robust Causation Discovery
Ruichu Cai, Zhenjie Zhang, Zhifeng Hao; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):208-216
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Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines
Kihyuk Sohn, Guanyu Zhou, Chansoo Lee, Honglak Lee; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):217-225
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Sequential Bayesian Search
Zheng Wen, Branislav Kveton, Brian Eriksson, Sandilya Bhamidipati; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):226-234
Sparse projections onto the simplex
Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):235-243
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Modeling Musical Influence with Topic Models
Uri Shalit, Daphna Weinshall, Gal Chechik; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):244-252
Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically
Mrinal Das, Suparna Bhattacharya, Chiranjib Bhattacharyya, Gopinath Kanchi; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):253-261
Exploring the Mind: Integrating Questionnaires and fMRI
Esther Salazar, Ryan Bogdan, Adam Gorka, Ahmad Hariri, Lawrence Carin; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):262-270
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A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions
Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):271-279
A Practical Algorithm for Topic Modeling with Provable Guarantees
Sanjeev Arora, Rong Ge, Yonatan Halpern, David Mimno, Ankur Moitra, David Sontag, Yichen Wu, Michael Zhu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):280-288
Distributed training of Large-scale Logistic models
Siddharth Gopal, Yiming Yang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):289-297
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An Adaptive Learning Rate for Stochastic Variational Inference
Rajesh Ranganath, Chong Wang, Blei David, Eric Xing; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):298-306
Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment
Billy Chang, Uwe Kruger, Rafal Kustra, Junping Zhang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):316-324
Large-Scale Learning with Less RAM via Randomization
Daniel Golovin, D. Sculley, Brendan McMahan, Michael Young; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):325-333
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Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization
Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):334-342
Sparse coding for multitask and transfer learning
Andreas Maurer, Massi Pontil, Bernardino Romera-Paredes; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):343-351
Direct Modeling of Complex Invariances for Visual Object Features
Ka Yu Hui; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):352-360
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Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data
Jan-Willem Meent, Jonathan Bronson, Frank Wood, Ruben Gonzalez Jr., Chris Wiggins; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):361-369
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Activized Learning with Uniform Classification Noise
Liu Yang, Steve Hanneke; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):370-378
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Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning
Gang Niu, Wittawat Jitkrittum, Bo Dai, Hirotaka Hachiya, Masashi Sugiyama; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):10-18
Gossip-based distributed stochastic bandit algorithms
Balazs Szorenyi, Robert Busa-Fekete, Istvan Hegedus, Robert Ormandi, Mark Jelasity, Balazs Kegl; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):19-27
The Sample-Complexity of General Reinforcement Learning
Tor Lattimore, Marcus Hutter, Peter Sunehag; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):28-36
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Hierarchical Regularization Cascade for Joint Learning
Alon Zweig, Daphna Weinshall; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):37-45
Multi-Class Classification with Maximum Margin Multiple Kernel
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):46-54
Bayesian Games for Adversarial Regression Problems
Michael Großhans, Christoph Sawade, Michael Brückner, Tobias Scheffer; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):55-63
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing
Xi Chen, Qihang Lin, Dengyong Zhou; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):64-72
Markov Network Estimation From Multi-attribute Data
Mladen Kolar, Han Liu, Eric Xing; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):73-81
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MILEAGE: Multiple Instance LEArning with Global Embedding
Dan Zhang, Jingrui He, Luo Si, Richard Lawrence; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):82-90
Guaranteed Sparse Recovery under Linear Transformation
Ji Liu, Lei Yuan, Jieping Ye; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):91-99
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Learning invariant features by harnessing the aperture problem
Roland Memisevic, Georgios Exarchakis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):100-108
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Efficient Ranking from Pairwise Comparisons
Fabian Wauthier, Michael Jordan, Nebojsa Jojic; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):109-117
Differentially Private Learning with Kernels
Prateek Jain, Abhradeep Thakurta; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):118-126
Thompson Sampling for Contextual Bandits with Linear Payoffs
Shipra Agrawal, Navin Goyal; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):127-135
Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space
Javier Almingol, Lui Montesano, Manuel Lopes; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):136-144
Inference algorithms for pattern-based CRFs on sequence data
Rustem Takhanov, Vladimir Kolmogorov; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):145-153
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One-Bit Compressed Sensing: Provable Support and Vector Recovery
Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):154-162
Tensor Analyzers
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey Hinton; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):163-171
Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression
Toby Hocking, Guillem Rigaill, Jean-Philippe Vert, Francis Bach; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):172-180
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Learning from Human-Generated Lists
Kwang-Sung Jun, Jerry Zhu, Burr Settles, Timothy Rogers; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):181-189
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A Fast and Exact Energy Minimization Algorithm for Cycle MRFs
Huayan Wang, Koller Daphne; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):190-198
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning
Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever, Rich Zemel; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):199-207
An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation
Nicholas Bryan, Gautham Mysore; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):208-216
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Estimating Unknown Sparsity in Compressed Sensing
Miles Lopes; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):217-225
MAD-Bayes: MAP-based Asymptotic Derivations from Bayes
Tamara Broderick, Brian Kulis, Michael Jordan; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):226-234
The Most Generative Maximum Margin Bayesian Networks
Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):235-243
Fastfood - Computing Hilbert Space Expansions in loglinear time
Quoc Le, Tamas Sarlos, Alexander Smola; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):244-252
Joint Transfer and Batch-mode Active Learning
Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, Jieping Ye; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):253-261
Message passing with l1 penalized KL minimization
Yuan Qi, Yandong Guo; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):262-270
Mean Reversion with a Variance Threshold
Marco Cuturi, Alexandre D’Aspremont; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):271-279
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Top-down particle filtering for Bayesian decision trees
Balaji Lakshminarayanan, Daniel Roy, Yee Whye Teh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):280-288
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations
Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):289-297
Robust and Discriminative Self-Taught Learning
Hua Wang, Feiping Nie, Heng Huang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):298-306
Safe Policy Iteration
Matteo Pirotta, Marcello Restelli, Alessio Pecorino, Daniele Calandriello; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):307-315
Unfolding Latent Tree Structures using 4th Order Tensors
Mariya Ishteva, Haesun Park, Le Song; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):316-324
Learning Fair Representations
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, Cynthia Dwork; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):325-333
Hierarchical Tensor Decomposition of Latent Tree Graphical Models
Le Song, Mariya Ishteva, Ankur Parikh, Eric Xing, Haesun Park; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):334-342
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No more pesky learning rates
Tom Schaul, Sixin Zhang, Yann LeCun; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):343-351
Multi-View Clustering and Feature Learning via Structured Sparsity
Hua Wang, Feiping Nie, Heng Huang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):352-360
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Planning by Prioritized Sweeping with Small Backups
Harm Van Seijen, Rich Sutton; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):361-369
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Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation
Sebastian Brechtel, Tobias Gindele, Rüdiger Dillmann; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):370-378
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Learning Heteroscedastic Models by Convex Programming under Group Sparsity
Arnak Dalalyan, Mohamed Hebiri, Katia Meziani, Joseph Salmon; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):379-387
Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels
Kai Zhang, Vincent Zheng, Qiaojun Wang, James Kwok, Qiang Yang, Ivan Marsic; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):388-395
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A Local Algorithm for Finding Well-Connected Clusters
Zeyuan Allen Zhu, Silvio Lattanzi, Vahab Mirrokni; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):396-404
Efficient Multi-label Classification with Many Labels
Wei Bi, James Kwok; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):405-413
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Spectral Compressed Sensing via Structured Matrix Completion
Yuxin Chen, Yuejie Chi; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):414-422
Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model
Ming Yang, Yingming Li, Zhongfei Zhang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):423-431
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Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images
Kyunghyun Cho; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):432-440
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On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions
Purushottam Kar, Bharath Sriperumbudur, Prateek Jain, Harish Karnick; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):441-449
Non-Linear Stationary Subspace Analysis with Application to Video Classification
Mahsa Baktashmotlagh, Mehrtash Harandi, Abbas Bigdeli, Brian Lovell, Mathieu Salzmann; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):450-458
Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy
Jean Honorio, Jaakkola Tommi; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):459-467
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That was fast! Speeding up NN search of high dimensional distributions.
Emanuele Coviello, Adeel Mumtaz, Antoni Chan, Gert Lanckriet; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):468-476
Entropic Affinities: Properties and Efficient Numerical Computation
Max Vladymyrov, Miguel Carreira-Perpinan; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):477-485
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction
Cijo Jose, Prasoon Goyal, Parv Aggrwal, Manik Varma; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):486-494
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Temporal Difference Methods for the Variance of the Reward To Go
Aviv Tamar, Dotan Di Castro, Shie Mannor; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):495-503
\proptoSVM for Learning with Label Proportions
Felix Yu, Dong Liu, Sanjiv Kumar, Jebara Tony, Shih-Fu Chang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):504-512
Parameter Learning and Convergent Inference for Dense Random Fields
Philipp Kraehenbuehl, Vladlen Koltun; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):513-521
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Loss-Proportional Subsampling for Subsequent ERM
Paul Mineiro, Nikos Karampatziakis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):522-530
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Scalable Simple Random Sampling and Stratified Sampling
Xiangrui Meng; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):531-539
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Riemannian Similarity Learning
Li Cheng; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):540-548
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On Compact Codes for Spatially Pooled Features
Yangqing Jia, Oriol Vinyals, Trevor Darrell; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):549-557
Dynamic Covariance Models for Multivariate Financial Time Series
Yue Wu, Jose Miguel Hernandez-Lobato, Ghahramani Zoubin; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):558-566
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Revisiting the Nystrom method for improved large-scale machine learning
Alex Gittens, Michael Mahoney; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):567-575
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Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals
Kazuyoshi Yoshii, Ryota Tomioka, Daichi Mochihashi, Masataka Goto; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):576-584
A Unified Robust Regression Model for Lasso-like Algorithms
Wenzhuo Yang, Huan Xu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):585-593
Quickly Boosting Decision Trees – Pruning Underachieving Features Early
Ron Appel, Thomas Fuchs, Piotr Dollar, Pietro Perona; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):594-602
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance
Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):603-611
Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment
Jason Chuang, Sonal Gupta, Christopher Manning, Jeffrey Heer; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):612-620
Online Kernel Learning with a Near Optimal Sparsity Bound
Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):621-629
Spectral Learning of Hidden Markov Models from Dynamic and Static Data
Tzu-Kuo Huang, Jeff Schneider; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):630-638
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Analogy-preserving Semantic Embedding for Visual Object Categorization
Sung Ju Hwang, Kristen Grauman, Fei Sha; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):639-647
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Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training
Michael Izbicki; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):648-656
Factorial Multi-Task Learning : A Bayesian Nonparametric Approach
Sunil Gupta, Dinh Phung, Svetha Venkatesh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):657-665
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Modeling Information Propagation with Survival Theory
Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):666-674
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Better Rates for Any Adversarial Deterministic MDP
Ofer Dekel, Elad Hazan; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):675-683
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ABC Reinforcement Learning
Christos Dimitrakakis, Nikolaos Tziortziotis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):684-692
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Sharp Generalization Error Bounds for Randomly-projected Classifiers
Robert Durrant, Ata Kaban; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):693-701
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On learning parametric-output HMMs
Aryeh Kontorovich, Boaz Nadler, Roi Weiss; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):702-710
LDA Topic Model with Soft Assignment of Descriptors to Words
Daphna Weinshall, Gal Levi, Dmitri Hanukaev; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):711-719
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On autoencoder scoring
Hanna Kamyshanska, Roland Memisevic; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):720-728
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Infinite Markov-Switching Maximum Entropy Discrimination Machines
Sotirios Chatzis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):729-737
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A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):738-746
Sparse PCA through Low-rank Approximations
Dimitris Papailiopoulos, Alexandros Dimakis, Stavros Korokythakis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):747-755
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Computation-Risk Tradeoffs for Covariance-Thresholded Regression
Dinah Shender, John Lafferty; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):756-764
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Exact Rule Learning via Boolean Compressed Sensing
Dmitry Malioutov, Kush Varshney; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):765-773
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Robust Sparse Regression under Adversarial Corruption
Yudong Chen, Constantine Caramanis, Shie Mannor; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):774-782
Optimization with First-Order Surrogate Functions
Julien Mairal; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):783-791
Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Anticipation
Hema Koppula, Ashutosh Saxena; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):792-800
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Consistency versus Realizable H-Consistency for Multiclass Classification
Phil Long, Rocco Servedio; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):801-809
Feature Multi-Selection among Subjective Features
Sivan Sabato, Adam Kalai; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):810-818
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Domain Adaptation under Target and Conditional Shift
Kun Zhang, Bernhard Schölkopf, Krikamol Muandet, Zhikun Wang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):819-827
Collective Stability in Structured Prediction: Generalization from One Example
Ben London, Bert Huang, Ben Taskar, Lise Getoor; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):828-836
Stable Coactive Learning via Perturbation
Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):837-845
Max-Margin Multiple-Instance Dictionary Learning
Xinggang Wang, Baoyuan Wang, Xiang Bai, Wenyu Liu, Zhuowen Tu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):846-854
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Fast Semidifferential-based Submodular Function Optimization
Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):855-863
Kernelized Bayesian Matrix Factorization
Mehmet Gönen, Suleiman Khan, Samuel Kaski; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):864-872
Learning the Structure of Sum-Product Networks
Robert Gens, Domingos Pedro; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):873-880
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Quantile Regression for Large-scale Applications
Jiyan Yang, Xiangrui Meng, Michael Mahoney; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):881-887
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Robust Regression on MapReduce
Xiangrui Meng, Michael Mahoney; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):888-896
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Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines
Kohei Ogawa, Motoki Imamura, Ichiro Takeuchi, Masashi Sugiyama; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):897-905
One-Pass AUC Optimization
Wei Gao, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):906-914
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Learning Convex QP Relaxations for Structured Prediction
Jeremy Jancsary, Sebastian Nowozin, Carsten Rother; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):915-923
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Concurrent Reinforcement Learning from Customer Interactions
David Silver, Leonard Newnham, David Barker, Suzanne Weller, Jason McFall; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):924-932
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Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner
Peng Sun, Jie Zhou; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):933-941
Stability and Hypothesis Transfer Learning
Ilja Kuzborskij, Francesco Orabona; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):942-950
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Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models
Mohammad Emtiyaz Khan, Aleksandr Aravkin, Michael Friedlander, Matthias Seeger; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):951-959
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Modeling Temporal Evolution and Multiscale Structure in Networks
Tue Herlau, Morten Mørup, Mikkel Schmidt; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):960-968
Dependent Normalized Random Measures
Changyou Chen, Vinayak Rao, Wray Buntine, Yee Whye Teh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):969-977
Fast Max-Margin Matrix Factorization with Data Augmentation
Minjie Xu, Jun Zhu, Bo Zhang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):978-986
Natural Image Bases to Represent Neuroimaging Data
Ashish Gupta, Murat Ayhan, Anthony Maida; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):987-994
Breaking the Small Cluster Barrier of Graph Clustering
Nir Ailon, Yudong Chen, Huan Xu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):995-1003
Approximate Inference in Collective Graphical Models
Daniel Sheldon, Tao Sun, Akshat Kumar, Tom Dietterich; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1004-1012
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Scaling the Indian Buffet Process via Submodular Maximization
Colorado Reed, Ghahramani Zoubin; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1013-1021
Mini-Batch Primal and Dual Methods for SVMs
Martin Takac, Avleen Bijral, Peter Richtarik, Nati Srebro; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1022-1030
The lasso, persistence, and cross-validation
Darren Homrighausen, Daniel McDonald; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1031-1039
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Spectral Experts for Estimating Mixtures of Linear Regressions
Arun Tejasvi Chaganty, Percy Liang; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1040-1048
Distribution to Distribution Regression
Junier Oliva, Barnabas Poczos, Jeff Schneider; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1049-1057
Regularization of Neural Networks using DropConnect
Li Wan, Matthew Zeiler, Sixin Zhang, Yann Le Cun, Rob Fergus; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1058-1066
Gaussian Process Kernels for Pattern Discovery and Extrapolation
Andrew Wilson, Ryan Adams; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1067-1075
Anytime Representation Learning
Zhixiang Xu, Matt Kusner, Gao Huang, Kilian Weinberger; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1076-1084
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Algorithms for Direct 0–1 Loss Optimization in Binary Classification
Tan Nguyen, Scott Sanner; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1085-1093
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Top-k Selection based on Adaptive Sampling of Noisy Preferences
Robert Busa-Fekete, Balazs Szorenyi, Weiwei Cheng, Paul Weng, Eyke Huellermeier; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1094-1102
The Extended Parameter Filter
Yusuf Bugra Erol, Lei Li, Bharath Ramsundar, Russell Stuart; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1103-1111
Exploiting Ontology Structures and Unlabeled Data for Learning
Nina Balcan, Avrim Blum, Yishay Mansour; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1112-1120
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions
Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1121-1129
Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization
Krzysztof Dembczynski, Arkadiusz Jachnik, Wojciech Kotlowski, Willem Waegeman, Eyke Huellermeier; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1130-1138
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, Geoffrey Hinton; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1139-1147
A non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines
Kostadin Georgiev, Preslav Nakov; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1148-1156
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Intersecting singularities for multi-structured estimation
Emile Richard, Francis BACH, Jean-Philippe Vert; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1157-1165
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
David Duvenaud, James Lloyd, Roger Grosse, Joshua Tenenbaum, Ghahramani Zoubin; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1166-1174
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Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events
Lisa Friedland, David Jensen, Michael Lavine; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1175-1183
Smooth Operators
Steffen Grunewalder, Gretton Arthur, John Shawe-Taylor; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1184-1192
The Cross-Entropy Method Optimizes for Quantiles
Sergiu Goschin, Ari Weinstein, Michael Littman; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1193-1201
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Topic Discovery through Data Dependent and Random Projections
Weicong Ding, Mohammad Hossein Rohban, Prakash Ishwar, Venkatesh Saligrama; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1202-1210
Bayesian Learning of Recursively Factored Environments
Marc Bellemare, Joel Veness, Michael Bowling; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1211-1219
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Selective sampling algorithms for cost-sensitive multiclass prediction
Alekh Agarwal; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1220-1228
The Bigraphical Lasso
Alfredo Kalaitzis, John Lafferty, Neil D. Lawrence, Shuheng Zhou; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1229-1237
Almost Optimal Exploration in Multi-Armed Bandits
Zohar Karnin, Tomer Koren, Oren Somekh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1238-1246
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Deep Canonical Correlation Analysis
Galen Andrew, Raman Arora, Jeff Bilmes, Karen Livescu; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1247-1255
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Consistency of Online Random Forests
Misha Denil, David Matheson, Nando Freitas; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1256-1264
Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting
Matt Wytock, Zico Kolter; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1265-1273
Fast Image Tagging
Minmin Chen, Alice Zheng, Kilian Weinberger; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1274-1282
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Expensive Function Optimization with Stochastic Binary Outcomes
Matthew Tesch, Jeff Schneider, Howie Choset; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1283-1291
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Multiple-source cross-validation
Krzysztof Geras, Charles Sutton; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1292-1300
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Learning Triggering Kernels for Multi-dimensional Hawkes Processes
Ke Zhou, Hongyuan Zha, Le Song; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1301-1309
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On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, Yoshua Bengio; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1310-1318
Maxout Networks
Ian Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1319-1327
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Predictable Dual-View Hashing
Mohammad Rastegari, Jonghyun Choi, Shobeir Fakhraei, Daume Hal, Larry Davis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1328-1336
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Deep learning with COTS HPC systems
Adam Coates, Brody Huval, Tao Wang, David Wu, Bryan Catanzaro, Ng Andrew; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1337-1345
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Nonparametric Mixture of Gaussian Processes with Constraints
James Ross, Jennifer Dy; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1346-1354
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Scale Invariant Conditional Dependence Measures
Sashank J Reddi, Barnabas Poczos; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1355-1363
Learning Policies for Contextual Submodular Prediction
Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, Drew Bagnell; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1364-1372
Manifold Preserving Hierarchical Topic Models for Quantization and Approximation
Minje Kim, Paris Smaragdis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1373-1381
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Safe Screening of Non-Support Vectors in Pathwise SVM Computation
Kohei Ogawa, Yoshiki Suzuki, Ichiro Takeuchi; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1382-1390
Cost-sensitive Multiclass Classification Risk Bounds
Bernardo Ávila Pires, Csaba Szepesvari, Mohammad Ghavamzadeh; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1391-1399
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Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion
Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil Jain; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1400-1408
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Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models
Umut Simsekli, Ali Taylan Cemgil, Yusuf Kenan Yilmaz; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1409-1417
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Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration
Volodymyr Kuleshov; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1418-1425
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Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling
Amr Ahmed, Liangjie Hong, Alexander Smola; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1426-1434
Tree-Independent Dual-Tree Algorithms
Ryan Curtin, William March, Parikshit Ram, David Anderson, Alexander Gray, Charles Isbell; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1435-1443
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Multilinear Multitask Learning
Bernardino Romera-Paredes, Hane Aung, Nadia Bianchi-Berthouze, Massimiliano Pontil; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1444-1452
Online Learning under Delayed Feedback
Pooria Joulani, Andras Gyorgy, Csaba Szepesvari; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1453-1461
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Adaptive Hamiltonian and Riemann Manifold Monte Carlo
Ziyu Wang, Shakir Mohamed, Nando Freitas; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1462-1470
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Coco-Q: Learning in Stochastic Games with Side Payments
Eric Sodomka, Elizabeth Hilliard, Michael Littman, Amy Greenwald; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1471-1479
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On A Nonlinear Generalization of Sparse Coding and Dictionary Learning
Jeffrey Ho, Yuchen Xie, Baba Vemuri; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1480-1488
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Estimation of Causal Peer Influence Effects
Panos Toulis, Edward Kao; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1489-1497
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