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Volume 28: International Conference on Machine Learning, 17-19 June 2013, Atlanta, Georgia, USA

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Editors: Sanjoy Dasgupta, David McAllester

[bib][citeproc]

Contents:

Cycle 1 Papers

An Optimal Policy for Target Localization with Application to Electron Microscopy

Raphael Sznitman, Aurelien Lucchi, Peter Frazier, Bruno Jedynak, Pascal Fua; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):1-9

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Human Boosting

Harsh Pareek, Pradeep Ravikumar; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):338-346

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Robust Structural Metric Learning

Daryl Lim, Gert Lanckriet, Brian McFee; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(1):615-623

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

Cycle 2 Papers

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

Stochastic Simultaneous Optimistic Optimization

Michal Valko, Alexandra Carpentier, Rémi Munos; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):19-27

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

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

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

Forecastable Component Analysis

Georg Goerg; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):64-72

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

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

Fast dropout training

Sida Wang, Christopher Manning; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):118-126

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

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

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

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

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

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

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

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

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

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

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

Margins, Shrinkage, and Boosting

Matus Telgarsky; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):307-315

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

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

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

Activized Learning with Uniform Classification Noise

Liu Yang, Steve Hanneke; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(2):370-378

Cycle 3 Papers

Guided Policy Search

Sergey Levine, Vladlen Koltun; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1-9

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Loss-Proportional Subsampling for Subsequent ERM

Paul Mineiro, Nikos Karampatziakis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):522-530

Scalable Simple Random Sampling and Stratified Sampling

Xiangrui Meng; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):531-539

Riemannian Similarity Learning

Li Cheng; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):540-548

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

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

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

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

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

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

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

ABC Reinforcement Learning

Christos Dimitrakakis, Nikolaos Tziortziotis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):684-692

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

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

On autoencoder scoring

Hanna Kamyshanska, Roland Memisevic; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):720-728

Infinite Markov-Switching Maximum Entropy Discrimination Machines

Sotirios Chatzis; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):729-737

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

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

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

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

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

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

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

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

Robust Regression on MapReduce

Xiangrui Meng, Michael Mahoney; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):888-896

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Multiple-source cross-validation

Krzysztof Geras, Charles Sutton; Proceedings of the 30th International Conference on Machine Learning, PMLR 28(3):1292-1300

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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