Volume 54: Artificial Intelligence and Statistics, 20-22 April 2017, Fort Lauderdale, FL, USA

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Editors: Aarti Singh, Jerry Zhu

[bib][citeproc]

Minimax Gaussian Classification & Clustering

Tianyang Li, Xinyang Yi, Constantine Carmanis, Pradeep Ravikumar ; PMLR 54:1-9

Conditions beyond treewidth for tightness of higher-order LP relaxations

Mark Rowland, Aldo Pacchiano, Adrian Weller ; PMLR 54:10-18

Large-Scale Data-Dependent Kernel Approximation

Catalin Ionescu, Alin Popa, Cristian Sminchisescu ; PMLR 54:19-27

Clustering from Multiple Uncertain Experts

Yale Chang, Junxiang Chen, Michael Cho, Peter Castaldi, Ed Silverman, Jennifer Dy ; PMLR 54:28-36

Online Nonnegative Matrix Factorization with General Divergences

Renbo Zhao, Vincent Tan, Huan Xu ; PMLR 54:37-45

ASAGA: Asynchronous Parallel SAGA

Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien ; PMLR 54:46-54

Lower Bounds on Active Learning for Graphical Model Selection

Jonathan Scarlett, Volkan Cevher ; PMLR 54:55-64

Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach

Dohyung Park, Anastasios Kyrillidis, Constantine Carmanis, Sujay Sanghavi ; PMLR 54:65-74

Sparse Accelerated Exponential Weights

Pierre Gaillard, Olivier Wintenberger ; PMLR 54:75-82

On the Learnability of Fully-Connected Neural Networks

Yuchen Zhang, Jason Lee, Martin Wainwright, Michael Jordan ; PMLR 54:83-91

An Information-Theoretic Route from Generalization in Expectation to Generalization in Probability

Ibrahim Alabdulmohsin ; PMLR 54:92-100

Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection

Lijie Chen, Jian Li, Mingda Qiao ; PMLR 54:101-110

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains

Andrew An Bian, Baharan Mirzasoleiman, Joachim Buhmann, Andreas Krause ; PMLR 54:111-120

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

Andrew Stevens, Yunchen Pu, Yannan Sun, Gregory Spell, Lawrence Carin ; PMLR 54:121-129

Consistent and Efficient Nonparametric Different-Feature Selection

Satoshi Hara, Takayuki Katsuki, Hiroki Yanagisawa, Takafumi Ono, Ryo Okamoto, Shigeki Takeuchi ; PMLR 54:130-138

Annular Augmentation Sampling

Francois Fagan, Jalaj Bhandari, John Cunningham ; PMLR 54:139-147

Less than a Single Pass: Stochastically Controlled Stochastic Gradient

Lihua Lei, Michael Jordan ; PMLR 54:148-156

Learning Time Series Detection Models from Temporally Imprecise Labels

Roy Adams, Ben Marlin ; PMLR 54:157-165

Learning Cost-Effective and Interpretable Treatment Regimes

Himabindu Lakkaraju, Cynthia Rudin ; PMLR 54:166-175

Linear Thompson Sampling Revisited

Marc Abeille, Alessandro Lazaric ; PMLR 54:176-184

A Sub-Quadratic Exact Medoid Algorithm

James Newling, Francois Fleuret ; PMLR 54:185-193

Minimax Density Estimation for Growing Dimension

Daniel McDonald ; PMLR 54:194-203

Estimating Density Ridges by Direct Estimation of Density-Derivative-Ratios

Hiroaki Sasaki, Takafumi Kanamori, Masashi Sugiyama ; PMLR 54:204-212

Learning Theory for Conditional Risk Minimization

Alexander Zimin, Christoph Lampert ; PMLR 54:213-222

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests

Yuxin Chen, Hamed Hassani, Andreas Krause ; PMLR 54:223-231

Learning Nash Equilibrium for General-Sum Markov Games from Batch Data

Julien Perolat, Florian Strub, Bilal Piot, Olivier Pietquin ; PMLR 54:232-241

Distance Covariance Analysis

Benjamin Cowley, Joao Semedo, Amin Zandvakili, Matthew Smith, Adam Kohn, Byron Yu ; PMLR 54:242-251

Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation

Sohail Bahmani, Justin Romberg ; PMLR 54:252-260

Regret Bounds for Lifelong Learning

Pierre Alquier, The Tien Mai, Massimiliano Pontil ; PMLR 54:261-269

Poisson intensity estimation with reproducing kernels

Seth Flaxman, Yee Whye Teh, Dino Sejdinovic ; PMLR 54:270-279

Generalized Pseudolikelihood Methods for Inverse Covariance Estimation

Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam ; PMLR 54:280-288

Removing Phase Transitions from Gibbs Measures

Ian Fellows, Mark Handcock ; PMLR 54:289-297

Performance Bounds for Graphical Record Linkage

Rebecca C. Steorts, Mattew Barnes, Willie Neiswanger ; PMLR 54:298-306

Regret Bounds for Transfer Learning in Bayesian Optimisation

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh ; PMLR 54:307-315

Scaling Submodular Maximization via Pruned Submodularity Graphs

Tianyi Zhou, Hua Ouyang, Jeff Blimes, Yi Chang, Carlos Guestrin ; PMLR 54:316-324

Localized Lasso for High-Dimensional Regression

Makoto Yamada, Takeuchi Koh, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski ; PMLR 54:325-333

Encrypted Accelerated Least Squares Regression

Pedro Esperanca, Louis Aslett, Chris Holmes ; PMLR 54:334-343

Random Consensus Robust PCA

Daniel Pimentel-Alarcon, Robert Nowak ; PMLR 54:344-352

Gray-box Inference for Structured Gaussian Process Models

Pietro Galliani, Amir Dezfouli, Edwin Bonilla, Novi Quadrianto ; PMLR 54:353-361

Frank-Wolfe Algorithms for Saddle Point Problems

Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien ; PMLR 54:362-371

A Framework for Optimal Matching for Causal Inference

Nathan Kallus ; PMLR 54:372-381

Quantifying the accuracy of approximate diffusions and Markov chains

Jonathan Huggins, James Zou ; PMLR 54:382-391

Stochastic Rank-1 Bandits

Sumeet Katariya, Branislav Kveton, Csaba Szepesvari, Claire Vernade, Zheng Wen ; PMLR 54:392-401

On the Troll-Trust Model for Edge Sign Prediction in Social Networks

Géraud Le Falher, Nicolo Cesa-Bianchi, Claudio Gentile, Fabio Vitale ; PMLR 54:402-411

Online Optimization of Smoothed Piecewise Constant Functions

Vincent Cohen-Addad, Varun Kanade ; PMLR 54:412-420

Combinatorial Topic Models using Small-Variance Asymptotics

Ke Jiang, Suvrit Sra, Brian Kulis ; PMLR 54:421-429

ConvNets with Smooth Adaptive Activation Functions for Regression

Le Hou, Dimitris Samaras, Tahsin Kurc, Yi Gao, Joel Saltz ; PMLR 54:430-439

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models

Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda ; PMLR 54:440-449

Efficient Rank Aggregation via Lehmer Codes

Pan Li, Arya Mazumdar, Olgica Milenkovic ; PMLR 54:450-459

Nonlinear ICA of Temporally Dependent Stationary Sources

Aapo Hyvarinen, Hiroshi Morioka ; PMLR 54:460-469

Stochastic Difference of Convex Algorithm and its Application to Training Deep Boltzmann Machines

Atsushi Nitanda, Taiji Suzuki ; PMLR 54:470-478

Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot

Prateek Jain, Chi Jin, Sham Kakade, Praneeth Netrapalli ; PMLR 54:479-488

Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms

Christian Naesseth, Francisco Ruiz, Scott Linderman, David Blei ; PMLR 54:489-498

Asymptotically exact inference in differentiable generative models

Matthew Graham, Amos Storkey ; PMLR 54:499-508

Decentralized Collaborative Learning of Personalized Models over Networks

Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi ; PMLR 54:509-517

Contextual Bandits with Latent Confounders: An NMF Approach

Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alex Dimakis, Sanjay Shakkottai ; PMLR 54:518-527

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets

Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter ; PMLR 54:528-536

Least-Squares Log-Density Gradient Clustering for Riemannian Manifolds

Mina Ashizawa, Hiroaki Sasaki, Tomoya Sakai, Masashi Sugiyama ; PMLR 54:537-546

Fast column generation for atomic norm regularization

Marina Vinyes, Guillaume Obozinski ; PMLR 54:547-556

Bayesian Hybrid Matrix Factorisation for Data Integration

Thomas Brouwer, Pietro Lio ; PMLR 54:557-566

Co-Occurring Directions Sketching for Approximate Matrix Multiply

Youssef Mroueh, Etienne Marcheret, Vaibahava Goel ; PMLR 54:567-575

Exploration-Exploitation in MDPs with Options

Ronan Fruit, Alessandro Lazaric ; PMLR 54:576-584

Local Perturb-and-MAP for Structured Prediction

Gedas Bertasius, Qiang Liu, Lorenzo Torresani, Jianbo Shi ; PMLR 54:585-594

Gradient Boosting on Stochastic Data Streams

Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, Andrew Bagnell ; PMLR 54:595-603

Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates

Joon Kwon, Vianney Perchet ; PMLR 54:604-613

Tensor Decompositions via Two-Mode Higher-Order SVD (HOSVD)

Miaoyan Wang, Yun Song ; PMLR 54:614-622

Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers

Meelis Kull, Telmo Silva Filho, Peter Flach ; PMLR 54:623-631

Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes

Feras Saad, Vikash Mansinghka ; PMLR 54:632-641

High-dimensional Time Series Clustering via Cross-Predictability

Dezhi Hong, Quanquan Gu, Kamin Whitehouse ; PMLR 54:642-651

Minimax Approach to Variable Fidelity Data Interpolation

Alexey Zaytsev, Evgeny Burnaev ; PMLR 54:652-661

Data Driven Resource Allocation for Distributed Learning

Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Nina Balcan, Alex Smola ; PMLR 54:662-671

Learning Nonparametric Forest Graphical Models with Prior Information

Yuancheng Zhu, Zhe Liu, Siqi Sun ; PMLR 54:672-680

Sparse Randomized Partition Trees for Nearest Neighbor Search

Kaushik Sinha, Omid Keivani ; PMLR 54:681-689

Horde of Bandits using Gaussian Markov Random Fields

Sharan Vaswani, Mark Schmidt, Laks Lakshmanan ; PMLR 54:690-699

Random projection design for scalable implicit smoothing of randomly observed stochastic processes

Francois Belletti, Evan Sparks, Alexandre Bayen, Joseph Gonzalez ; PMLR 54:700-708

Trading off Rewards and Errors in Multi-Armed Bandits

Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu ; PMLR 54:709-717

Adaptive ADMM with Spectral Penalty Parameter Selection

Zheng Xu, Mario Figueiredo, Tom Goldstein ; PMLR 54:718-727

The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits

Tor Lattimore, Csaba Szepesvari ; PMLR 54:728-737

Dynamic Collaborative Filtering With Compound Poisson Factorization

Ghassen Jerfel, Mehmet Basbug, Barbara Engelhardt ; PMLR 54:738-747

Rank Aggregation and Prediction with Item Features

Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit Dhillon ; PMLR 54:748-756

Robust and Efficient Computation of Eigenvectors in a Generalized Spectral Method for Constrained Clustering

Chengming Jiang, Huiqing Xie, Zhaojun Bai ; PMLR 54:757-766

Information-theoretic limits of Bayesian network structure learning

Asish Ghoshal, Jean Honorio ; PMLR 54:767-775

Markov Chain Truncation for Doubly-Intractable Inference

Colin Wei, Iain Murray ; PMLR 54:776-784

Regression Uncertainty on the Grassmannian

Yi Hong, Xiao Yang, Roland Kwitt, Martin Styner, Marc Niethammer ; PMLR 54:785-793

Attributing Hacks

Ziqi Liu, Alex Smola, Kyle Soska, Yu-Xiang Wang, Qinghua Zheng ; PMLR 54:794-802

Unsupervised Sequential Sensor Acquisition

Manjesh Hanawal, Csaba Szepesvari, Venkatesh Saligrama ; PMLR 54:803-811

A Stochastic Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization

Songtao Lu, Mingyi Hong, Zhengdao Wang ; PMLR 54:812-821

Hierarchically-partitioned Gaussian Process Approximation

Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim ; PMLR 54:822-831

Scalable Learning of Non-Decomposable Objectives

Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan ; PMLR 54:832-840

CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC

Tianfan Fu, Zhihua Zhang ; PMLR 54:841-850

Comparison-Based Nearest Neighbor Search

Siavash Haghiri, Debarghya Ghoshdastidar, Ulrike von Luxburg ; PMLR 54:851-859

A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe

Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi ; PMLR 54:860-868

Faster Coordinate Descent via Adaptive Importance Sampling

Dmytro Perekrestenko, Volkan Cevher, Martin Jaggi ; PMLR 54:869-877

Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models

Mohammad Khan, Wu Lin ; PMLR 54:878-887

Hit-and-Run for Sampling and Planning in Non-Convex Spaces

Yasin Abbasi-Yadkori, Peter Bartlett, Victor Gabillon, Alan Malek ; PMLR 54:888-895

DP-EM: Differentially Private Expectation Maximization

Mijung Park, James Foulds, Kamalika Choudhary, Max Welling ; PMLR 54:896-904

On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior

Juho Piironen, Aki Vehtari ; PMLR 54:905-913

Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems

Scott Linderman, Matthew Johnson, Andrew Miller, Ryan Adams, David Blei, Liam Paninski ; PMLR 54:914-922

Efficient Algorithm for Sparse Tensor-variate Gaussian Graphical Models via Gradient Descent

Pan Xu, Tingting Zhang, Quanquan Gu ; PMLR 54:923-932

Minimax-optimal semi-supervised regression on unknown manifolds

Amit Moscovich, Ariel Jaffe, Nadler Boaz ; PMLR 54:933-942

Improved Strongly Adaptive Online Learning using Coin Betting

Kwang-Sung Jun, Francesco Orabona, Stephen Wright, Rebecca Willett ; PMLR 54:943-951

Black-box Importance Sampling

Qiang Liu, Jason Lee ; PMLR 54:952-961

Fairness Constraints: Mechanisms for Fair Classification

Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rogriguez, Krishna P. Gummadi ; PMLR 54:962-970

Frequency Domain Predictive Modelling with Aggregated Data

Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo ; PMLR 54:971-980

A Unified Computational and Statistical Framework for Nonconvex Low-rank Matrix Estimation

Lingxiao Wang, Xiao Zhang, Quanquan Gu ; PMLR 54:981-990

A New Class of Private Chi-Square Hypothesis Tests

Ryan Rogers, Daniel Kifer ; PMLR 54:991-1000

A Learning Theory of Ranking Aggregation

Anna Korba, Stéphan Clemencon, Eric Sibony ; PMLR 54:1001-1010

Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere

Albert Thomas, Stéphan Clemencon, Alexandre Gramfort, Anne Sabourin ; PMLR 54:1011-1019

Structured adaptive and random spinners for fast machine learning computations

Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cedric Gouy-Pailler, Anne Morvan, Nouri Sakr, Tamas Sarlos, Jamal Atif ; PMLR 54:1020-1029

Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification

Aleksandar Botev, Bowen Zheng, David Barber ; PMLR 54:1030-1038

Learning Optimal Interventions

Jonas Mueller, David Reshef, George Du, Tommi Jaakkola ; PMLR 54:1039-1047

A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case

Nicholas Ruozzi ; PMLR 54:1048-1056

Scalable Variational Inference for Super Resolution Microscopy

Ruoxi Sun, Evan Archer, Liam Paninski ; PMLR 54:1057-1065

Linear Convergence of Stochastic Frank Wolfe Variants

Donald Goldfarb, Garud Iyengar, Chaoxu Zhou ; PMLR 54:1066-1074

Sequential Graph Matching with Sequential Monte Carlo

Seong-Hwan Jun, Samuel W.K. Wong, James Zidek, Alexandre Bouchard-Cote ; PMLR 54:1075-1084

Fast rates with high probability in exp-concave statistical learning

Nishant Mehta ; PMLR 54:1085-1093

Generalization Error of Invariant Classifiers

Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel Rodrigues ; PMLR 54:1094-1103

Learning with Feature Feedback: from Theory to Practice

Stefanos Poulis, Sanjoy Dasgupta ; PMLR 54:1104-1113

Optimistic Planning for the Stochastic Knapsack Problem

Ciara Pike-Burke, Steffen Grunewalder ; PMLR 54:1114-1122

Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted $L_1$-norms

Raman Sankaran, Francis Bach, Chiranjib Bhattacharya ; PMLR 54:1123-1131

Tracking Objects with Higher Order Interactions via Delayed Column Generation

Shaofei Wang, Steffen Wolf, Charless Fowlkes, Julian Yarkony ; PMLR 54:1132-1140

Belief Propagation in Conditional RBMs for Structured Prediction

Wei Ping, Alex Ihler ; PMLR 54:1141-1149

Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data

Jialei Wang, Jason Lee, Mehrdad Mahdavi, Mladen Kolar, Nati Srebro ; PMLR 54:1150-1158

Finite-sum Composition Optimization via Variance Reduced Gradient Descent

Xiangru Lian, Mengdi Wang, Ji Liu ; PMLR 54:1159-1167

A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models

Beilun Wang, Ji Gao, Yanjun Qi ; PMLR 54:1168-1177

Communication-efficient Distributed Sparse Linear Discriminant Analysis

Lu Tian, Quanquan Gu ; PMLR 54:1178-1187

Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage

Alp Yurtsever, Madeleine Udell, Joel Tropp, Volkan Cevher ; PMLR 54:1188-1196

Modal-set estimation with an application to clustering

Heinrich Jiang, Samory Kpotufe ; PMLR 54:1197-1206

Compressed Least Squares Regression revisited

Martin Slawski ; PMLR 54:1207-1215

Diverse Neural Network Learns True Target Functions

Bo Xie, Yingyu Liang, Le Song ; PMLR 54:1216-1224

Local Group Invariant Representations via Orbit Embeddings

Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schoelkopf ; PMLR 54:1225-1235

Relativistic Monte Carlo

Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian Vollmer ; PMLR 54:1236-1245

Thompson Sampling for Linear-Quadratic Control Problems

Marc Abeille, Alessandro Lazaric ; PMLR 54:1246-1254

Fast Classification with Binary Prototypes

Kai Zhong, Ruiqi Guo, Sanjiv Kumar, Bowei Yan, David Simcha, Inderjit Dhillon ; PMLR 54:1255-1263

Prediction Performance After Learning in Gaussian Process Regression

Johan Wagberg, Dave Zachariah, Thomas Schon, Petre Stoica ; PMLR 54:1264-1272

Communication-Efficient Learning of Deep Networks from Decentralized Data

Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Aguera y Arcas ; PMLR 54:1273-1282

Learning Structured Weight Uncertainty in Bayesian Neural Networks

Shengyang Sun, Changyou Chen, Lawrence Carin ; PMLR 54:1283-1292

Signal-based Bayesian Seismic Monitoring

David Moore, Stuart Russell ; PMLR 54:1293-1301

Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields

Youngsuk Park, David Hallac, Stephen Boyd, Jure Leskovec ; PMLR 54:1302-1310

Discovering and Exploiting Additive Structure for Bayesian Optimization

Jacob Gardner, Chuan Guo, Kilian Weinberger, Roman Garnett, Roger Grosse ; PMLR 54:1311-1319

Lipschitz Density-Ratios, Structured Data, and Data-driven Tuning

Samory Kpotufe ; PMLR 54:1320-1328

Spatial Decompositions for Large Scale SVMs

Philipp Thomann, Ingrid Blaschzyk, Mona Meister, Ingo Steinwart ; PMLR 54:1329-1337

Inference Compilation and Universal Probabilistic Programming

Tuan Anh Le, Atilim Gunes Baydin, Frank Wood ; PMLR 54:1338-1348

Active Positive Semidefinite Matrix Completion: Algorithms, Theory and Applications

Aniruddha Bhargava, Ravi Ganti, Rob Nowak ; PMLR 54:1349-1357

Information Projection and Approximate Inference for Structured Sparse Variables

Rajiv Khanna, Joydeep Ghosh, Rusell Poldrack, Oluwasanmi Koyejo ; PMLR 54:1358-1366

On the Interpretability of Conditional Probability Estimates in the Agnostic Setting

Yihan Gao, Aditya Parameswaran, Jian Peng ; PMLR 54:1367-1374

Linking Micro Event History to Macro Prediction in Point Process Models

Yichen Wang, Xiaojing Ye, Haomin Zhou, Hongyuan Zha, Le Song ; PMLR 54:1375-1384

Initialization and Coordinate Optimization for Multi-way Matching

Da Tang, Tony Jebara ; PMLR 54:1385-1393

Optimal Recovery of Tensor Slices

Vivek Farias, Andrew Li ; PMLR 54:1394-1402

Efficient Online Multiclass Prediction on Graphs via Surrogate Losses

Alexander Rakhlin, Karthik Sridharan ; PMLR 54:1403-1411

Distribution of Gaussian Process Arc Lengths

Justin Bewsher, Alessandra Tosi, Michael Osborne, Stephen Roberts ; PMLR 54:1412-1420

Distributed Adaptive Sampling for Kernel Matrix Approximation

Daniele Calandriello, Alessandro Lazaric, Michal Valko ; PMLR 54:1421-1429

Binary and Multi-Bit Coding for Stable Random Projections

Ping Li ; PMLR 54:1430-1438

Spectral Methods for Correlated Topic Models

Forough Arabshahi, Anima Anandkumar ; PMLR 54:1439-1447

Label Filters for Large Scale Multilabel Classification

Alexandru Niculescu-Mizil, Ehsan Abbasnejad ; PMLR 54:1448-1457

Learning from Conditional Distributions via Dual Embeddings

Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song ; PMLR 54:1458-1467

Sequential Multiple Hypothesis Testing with Type I Error Control

Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh ; PMLR 54:1468-1476

A Maximum Matching Algorithm for Basis Selection in Spectral Learning

Ariadna Quattoni, Xavier Carreras, Matthias Gallé ; PMLR 54:1477-1485

Value-Aware Loss Function for Model-based Reinforcement Learning

Amir-Massoud Farahmand, Andre Barreto, Daniel Nikovski ; PMLR 54:1486-1494

Convergence Rate of Stochastic k-means

Cheng Tang, Claire Monteleoni ; PMLR 54:1495-1503

Automated Inference with Adaptive Batches

Soham De, Abhay Yadav, David Jacobs, Tom Goldstein ; PMLR 54:1504-1513

Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition

Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar, Inderjit Dhillon ; PMLR 54:1514-1522

Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness

Ioan Gabriel Bucur, Tom Claassen, Tom Heskes ; PMLR 54:1523-1531

Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions

Asish Ghoshal, Jean Honorio ; PMLR 54:1532-1540

Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models

Ankit Anand, Ritesh Noothigattu, Parag Singla, Mausam ; PMLR 54:1541-1549

Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain

Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang, Qixing Huang, Pradeep Ravikumar, Inderjit Dhillon ; PMLR 54:1550-1559

Scalable Greedy Feature Selection via Weak Submodularity

Rajiv Khanna, Ethan Elenberg, Alex Dimakis, Sahand Negahban, Joydeep Ghosh ; PMLR 54:1560-1568

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