[edit]

Volume 32: International Conference on Machine Learning, 22-24 June 2014, Bejing, China

[edit]

Editors: Eric P. Xing, Tony Jebara

[bib][citeproc]

Contents:

Cycle 1 Papers

A Discriminative Latent Variable Model for Online Clustering

Rajhans Samdani, Kai-Wei Chang, Dan Roth; PMLR 32(1):1-9

Kernel Mean Estimation and Stein Effect

Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton, Bernhard Schoelkopf; PMLR 32(1):10-18

Demystifying Information-Theoretic Clustering

Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo; PMLR 32(1):19-27

Covering Number for Efficient Heuristic-based POMDP Planning

Zongzhang Zhang, David Hsu, Wee Sun Lee; PMLR 32(1):28-36

The Coherent Loss Function for Classification

Wenzhuo Yang, Melvyn Sim, Huan Xu; PMLR 32(1):37-45

Fast Stochastic Alternating Direction Method of Multipliers

Wenliang Zhong, James Kwok; PMLR 32(1):46-54

Active Detection via Adaptive Submodularity

Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause; PMLR 32(1):55-63

Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization

Shai Shalev-Shwartz, Tong Zhang; PMLR 32(1):64-72

An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization

Qihang Lin, Lin Xiao; PMLR 32(1):73-81

Recurrent Convolutional Neural Networks for Scene Labeling

Pedro Pinheiro, Ronan Collobert; PMLR 32(1):82-90

A Statistical Perspective on Algorithmic Leveraging

Ping Ma, Michael Mahoney, Bin Yu; PMLR 32(1):91-99

Thompson Sampling for Complex Online Problems

Aditya Gopalan, Shie Mannor, Yishay Mansour; PMLR 32(1):100-108

Boosting multi-step autoregressive forecasts

Souhaib Ben Taieb, Rob Hyndman; PMLR 32(1):109-117

A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data

Arun Rajkumar, Shivani Agarwal; PMLR 32(1):118-126

Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations

Timothy Mann, Shie Mannor; PMLR 32(1):127-135

Latent Bandits.

Odalric-Ambrym Maillard, Shie Mannor; PMLR 32(1):136-144

Fast Allocation of Gaussian Process Experts

Trung Nguyen, Edwin Bonilla; PMLR 32(1):145-153

Von Mises-Fisher Clustering Models

Siddharth Gopal, Yiming Yang; PMLR 32(1):154-162

Convergence rates for persistence diagram estimation in Topological Data Analysis

Frédéric Chazal, Marc Glisse, Catherine Labruère, Bertrand Michel; PMLR 32(1):163-171

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs

Fabian Gieseke, Justin Heinermann, Cosmin Oancea, Christian Igel; PMLR 32(1):172-180

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget

Anoop Korattikara, Yutian Chen, Max Welling; PMLR 32(1):181-189

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis

Jian Tang, Zhaoshi Meng, Xuanlong Nguyen, Qiaozhu Mei, Ming Zhang; PMLR 32(1):190-198

The Inverse Regression Topic Model

Maxim Rabinovich, David Blei; PMLR 32(1):199-207

A Consistent Histogram Estimator for Exchangeable Graph Models

Stanley Chan, Edoardo Airoldi; PMLR 32(1):208-216

Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data

Benjamin Letham, Wei Sun, Anshul Sheopuri; PMLR 32(1):217-225

Towards Minimax Online Learning with Unknown Time Horizon

Haipeng Luo, Robert Schapire; PMLR 32(1):226-234

Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball

Andrew Miller, Luke Bornn, Ryan Adams, Kirk Goldsberry; PMLR 32(1):235-243

Margins, Kernels and Non-linear Smoothed Perceptrons

Aaditya Ramdas, Javier Peña; PMLR 32(1):244-252

Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models

Shike Mei, Jun Zhu, Jerry Zhu; PMLR 32(1):253-261

Learning Theory and Algorithms for revenue optimization in second price auctions with reserve

Mehryar Mohri, Andres Munoz Medina; PMLR 32(1):262-270

Low-density Parity Constraints for Hashing-Based Discrete Integration

Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman; PMLR 32(1):271-279

Prediction with Limited Advice and Multiarmed Bandits with Paid Observations

Yevgeny Seldin, Peter Bartlett, Koby Crammer, Yasin Abbasi-Yadkori; PMLR 32(1):280-287

Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts

Tien Vu Nguyen, Dinh Phung, Xuanlong Nguyen, Swetha Venkatesh, Hung Bui; PMLR 32(1):288-296

Large-Margin Metric Learning for Constrained Partitioning Problems

Rémi Lajugie, Francis Bach, Sylvain Arlot; PMLR 32(1):297-305

Wasserstein Propagation for Semi-Supervised Learning

Justin Solomon, Raif Rustamov, Leonidas Guibas, Adrian Butscher; PMLR 32(1):306-314

Max-Margin Infinite Hidden Markov Models

Aonan Zhang, Jun Zhu, Bo Zhang; PMLR 32(1):315-323

Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function

Yong Liu, Shali Jiang, Shizhong Liao; PMLR 32(1):324-332

Generalized Exponential Concentration Inequality for Renyi Divergence Estimation

Shashank Singh, Barnabas Poczos; PMLR 32(1):333-341

Boosting with Online Binary Learners for the Multiclass Bandit Problem

Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu; PMLR 32(1):342-350

Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm

Tasuku Soma, Naonori Kakimura, Kazuhiro Inaba, Ken-ichi Kawarabayashi; PMLR 32(1):351-359

Computing Parametric Ranking Models via Rank-Breaking

Hossein Azari Soufiani, David Parkes, Lirong Xia; PMLR 32(1):360-368

Tracking Adversarial Targets

Yasin Abbasi-Yadkori, Peter Bartlett, Varun Kanade; PMLR 32(1):369-377

Online Bayesian Passive-Aggressive Learning

Tianlin Shi, Jun Zhu; PMLR 32(1):378-386

Deterministic Policy Gradient Algorithms

David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin Riedmiller; PMLR 32(1):387-395

Modeling Correlated Arrival Events with Latent Semi-Markov Processes

Wenzhao Lian, Vinayak Rao, Brian Eriksson, Lawrence Carin; PMLR 32(1):396-404

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach

Rémi Bardenet, Arnaud Doucet, Chris Holmes; PMLR 32(1):405-413

Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost

Ferdinando Cicalese, Eduardo Laber, Aline Medeiros Saettler; PMLR 32(1):414-422

Condensed Filter Tree for Cost-Sensitive Multi-Label Classification

Chun-Liang Li, Hsuan-Tien Lin; PMLR 32(1):423-431

On Measure Concentration of Random Maximum A-Posteriori Perturbations

Francesco Orabona, Tamir Hazan, Anand Sarwate, Tommi Jaakkola; PMLR 32(1):432-440

Bias in Natural Actor-Critic Algorithms

Philip Thomas; PMLR 32(1):441-448

Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning

François Denis, Mattias Gybels, Amaury Habrard; PMLR 32(1):449-457

On Modelling Non-linear Topical Dependencies

Zhixing Li, Siqiang Wen, Juanzi Li, Peng Zhang, Jie Tang; PMLR 32(1):458-466

A Deep and Tractable Density Estimator

Benigno Uria, Iain Murray, Hugo Larochelle; PMLR 32(1):467-475

(Near) Dimension Independent Risk Bounds for Differentially Private Learning

Prateek Jain, Abhradeep Guha Thakurta; PMLR 32(1):476-484

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels

Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael Mahoney; PMLR 32(1):485-493

Discriminative Features via Generalized Eigenvectors

Nikos Karampatziakis, Paul Mineiro; PMLR 32(1):494-502

Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint

Ji Liu, Jieping Ye, Ryohei Fujimaki; PMLR 32(1):503-511

Online Learning in Markov Decision Processes with Changing Cost Sequences

Travis Dick, Andras Gyorgy, Csaba Szepesvari; PMLR 32(1):512-520

Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms

Richard Combes, Alexandre Proutiere; PMLR 32(1):521-529

Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection

Arun Iyer, Saketha Nath, Sunita Sarawagi; PMLR 32(1):530-538

Asymptotically consistent estimation of the number of change points in highly dependent time series

Azadeh Khaleghi, Daniil Ryabko; PMLR 32(1):539-547

Coordinate-descent for learning orthogonal matrices through Givens rotations

Uri Shalit, Gal Chechik; PMLR 32(1):548-556

Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search

Anshumali Shrivastava, Ping Li; PMLR 32(1):557-565

A Divide-and-Conquer Solver for Kernel Support Vector Machines

Cho-Jui Hsieh, Si Si, Inderjit Dhillon; PMLR 32(1):566-574

Nuclear Norm Minimization via Active Subspace Selection

Cho-Jui Hsieh, Peder Olsen; PMLR 32(1):575-583

Provable Bounds for Learning Some Deep Representations

Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma; PMLR 32(1):584-592

Large-scale Multi-label Learning with Missing Labels

Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit Dhillon; PMLR 32(1):593-601

Learning Graphs with a Few Hubs

Rashish Tandon, Pradeep Ravikumar; PMLR 32(1):602-610

Agnostic Bayesian Learning of Ensembles

Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle; PMLR 32(1):611-619

Towards an optimal stochastic alternating direction method of multipliers

Samaneh Azadi, Suvrit Sra; PMLR 32(1):620-628

Spherical Hamiltonian Monte Carlo for Constrained Target Distributions

Shiwei Lan, Bo Zhou, Babak Shahbaba; PMLR 32(1):629-637

Efficient Continuous-Time Markov Chain Estimation

Monir Hajiaghayi, Bonnie Kirkpatrick, Liangliang Wang, Alexandre Bouchard-Côté; PMLR 32(1):638-646

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell; PMLR 32(1):647-655

Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers

Dani Yogatama, Noah Smith; PMLR 32(1):656-664

Narrowing the Gap: Random Forests In Theory and In Practice

Misha Denil, David Matheson, Nando De Freitas; PMLR 32(1):665-673

Coherent Matrix Completion

Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward; PMLR 32(1):674-682

Admixture of Poisson MRFs: A Topic Model with Word Dependencies

David Inouye, Pradeep Ravikumar, Inderjit Dhillon; PMLR 32(1):683-691

True Online TD(lambda)

Harm Seijen, Rich Sutton; PMLR 32(1):692-700

Memory Efficient Kernel Approximation

Si Si, Cho-Jui Hsieh, Inderjit Dhillon; PMLR 32(1):701-709

Learning Sum-Product Networks with Direct and Indirect Variable Interactions

Amirmohammad Rooshenas, Daniel Lowd; PMLR 32(1):710-718

Hamiltonian Monte Carlo Without Detailed Balance

Jascha Sohl-Dickstein, Mayur Mudigonda, Michael DeWeese; PMLR 32(1):719-726

Filtering with Abstract Particles

Jacob Steinhardt, Percy Liang; PMLR 32(1):727-735

Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers

Taiji Suzuki; PMLR 32(1):736-744

Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction

Jian Zhou, Olga Troyanskaya; PMLR 32(1):745-753

An Efficient Approach for Assessing Hyperparameter Importance

Frank Hutter, Holger Hoos, Kevin Leyton-Brown; PMLR 32(1):754-762

Cycle 2 Papers

An Information Geometry of Statistical Manifold Learning

Ke Sun, Stéphane Marchand-Maillet; PMLR 32(2):1-9

Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem

Masrour Zoghi, Shimon Whiteson, Remi Munos, Maarten Rijke; PMLR 32(2):10-18

Compact Random Feature Maps

Raffay Hamid, Ying Xiao, Alex Gittens, Dennis Decoste; PMLR 32(2):19-27

Concentration in unbounded metric spaces and algorithmic stability

Aryeh Kontorovich; PMLR 32(2):28-36

Heavy-tailed regression with a generalized median-of-means

Daniel Hsu, Sivan Sabato; PMLR 32(2):37-45

Spectral Bandits for Smooth Graph Functions

Michal Valko, Remi Munos, Branislav Kveton, Tomáš Kocák; PMLR 32(2):46-54

Robust Principal Component Analysis with Complex Noise

Qian Zhao, Deyu Meng, Zongben Xu, Wangmeng Zuo, Lei Zhang; PMLR 32(2):55-63

Scalable Semidefinite Relaxation for Maximum A Posterior Estimation

Qixing Huang, Yuxin Chen, Leonidas Guibas; PMLR 32(2):64-72

Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery

Cun Mu, Bo Huang, John Wright, Donald Goldfarb; PMLR 32(2):73-81

Automated inference of point of view from user interactions in collective intelligence venues

Sanmay Das, Allen Lavoie; PMLR 32(2):82-90

Rank-One Matrix Pursuit for Matrix Completion

Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, Jieping Ye; PMLR 32(2):91-99

Near-Optimal Joint Object Matching via Convex Relaxation

Yuxin Chen, Leonidas Guibas, Qixing Huang; PMLR 32(2):100-108

Convex Total Least Squares

Dmitry Malioutov, Nikolai Slavov; PMLR 32(2):109-117

On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection

Pratik Jawanpuria, Manik Varma, Saketha Nath; PMLR 32(2):118-126

Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization

Xiaotong Yuan, Ping Li, Tong Zhang; PMLR 32(2):127-135

A Unified Framework for Consistency of Regularized Loss Minimizers

Jean Honorio, Tommi Jaakkola; PMLR 32(2):136-144

Geodesic Distance Function Learning via Heat Flow on Vector Fields

Binbin Lin, Ji Yang, Xiaofei He, Jieping Ye; PMLR 32(2):145-153

Near-Optimally Teaching the Crowd to Classify

Adish Singla, Ilija Bogunovic, Gabor Bartok, Amin Karbasi, Andreas Krause; PMLR 32(2):154-162

On the convergence of no-regret learning in selfish routing

Walid Krichene, Benjamin Drighès, Alexandre Bayen; PMLR 32(2):163-171

Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques

Jérémie Mary, Philippe Preux, Olivier Nicol; PMLR 32(2):172-180

Scaling Up Robust MDPs using Function Approximation

Aviv Tamar, Shie Mannor, Huan Xu; PMLR 32(2):181-189

Marginal Structured SVM with Hidden Variables

Wei Ping, Qiang Liu, Alex Ihler; PMLR 32(2):190-198

Linear and Parallel Learning of Markov Random Fields

Yariv Mizrahi, Misha Denil, Nando De Freitas; PMLR 32(2):199-207

Pitfalls in the use of Parallel Inference for the Dirichlet Process

Yarin Gal, Zoubin Ghahramani; PMLR 32(2):208-216

Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing

Yuan Zhou, Xi Chen, Jian Li; PMLR 32(2):217-225

Deep Generative Stochastic Networks Trainable by Backprop

Yoshua Bengio, Eric Laufer, Guillaume Alain, Jason Yosinski; PMLR 32(2):226-234

A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models

Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, Jieping Ye; PMLR 32(2):235-243

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting

Yudong Chen, Jiaming Xu; PMLR 32(2):244-252

Gaussian Process Optimization with Mutual Information

Emile Contal, Vianney Perchet, Nicolas Vayatis; PMLR 32(2):253-261

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy

Dengyong Zhou, Qiang Liu, John Platt, Christopher Meek; PMLR 32(2):262-270

Exchangeable Variable Models

Mathias Niepert, Pedro Domingos; PMLR 32(2):271-279

Clustering in the Presence of Background Noise

Shai Ben-David, Nika Haghtalab; PMLR 32(2):280-288

Safe Screening with Variational Inequalities and Its Application to Lasso

Jun Liu, Zheng Zhao, Jie Wang, Jieping Ye; PMLR 32(2):289-297

Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks

Shan-Hung Wu, Hao-Heng Chien, Kuan-Hua Lin, Philip Yu; PMLR 32(2):298-306

Signal recovery from Pooling Representations

Joan Bruna Estrach, Arthur Szlam, Yann LeCun; PMLR 32(2):307-315

PAC-inspired Option Discovery in Lifelong Reinforcement Learning

Emma Brunskill, Lihong Li; PMLR 32(2):316-324

Multi-label Classification via Feature-aware Implicit Label Space Encoding

Zijia Lin, Guiguang Ding, Mingqing Hu, Jianmin Wang; PMLR 32(2):325-333

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications

Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani; PMLR 32(2):334-342

Anomaly Ranking as Supervised Bipartite Ranking

Stephan Clémençon, Sylvain Robbiano; PMLR 32(2):343-351

Hierarchical Quasi-Clustering Methods for Asymmetric Networks

Gunnar Carlsson, Facundo Mémoli, Alejandro Ribeiro, Santiago Segarra; PMLR 32(2):352-360

Rectangular Tiling Process

Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura, Takeshi Yamada, Naonori Ueda; PMLR 32(2):361-369

Two-Stage Metric Learning

Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis; PMLR 32(2):370-378

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices

Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani; PMLR 32(2):379-387

Elementary Estimators for High-Dimensional Linear Regression

Eunho Yang, Aurelie Lozano, Pradeep Ravikumar; PMLR 32(2):388-396

Elementary Estimators for Sparse Covariance Matrices and other Structured Moments

Eunho Yang, Aurelie Lozano, Pradeep Ravikumar; PMLR 32(2):397-405

Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically

Yuan Fang, Kevin Chang, Hady Lauw; PMLR 32(2):406-414

Bayesian Max-margin Multi-Task Learning with Data Augmentation

Chengtao Li, Jun Zhu, Jianfei Chen; PMLR 32(2):415-423

Sparse Reinforcement Learning via Convex Optimization

Zhiwei Qin, Weichang Li, Firdaus Janoos; PMLR 32(2):424-432

Gaussian Process Classification and Active Learning with Multiple Annotators

Filipe Rodrigues, Francisco Pereira, Bernardete Ribeiro; PMLR 32(2):433-441

Structured Prediction of Network Response

Hongyu Su, Aristides Gionis, Juho Rousu; PMLR 32(2):442-450

An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy

Gavin Taylor, Connor Geer, David Piekut; PMLR 32(2):451-459

Optimization Equivalence of Divergences Improves Neighbor Embedding

Zhirong Yang, Jaakko Peltonen, Samuel Kaski; PMLR 32(2):460-468

An Asynchronous Parallel Stochastic Coordinate Descent Algorithm

Ji Liu, Steve Wright, Christopher Re, Victor Bittorf, Srikrishna Sridhar; PMLR 32(2):469-477

Consistency of Causal Inference under the Additive Noise Model

Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing, Bernhard Schölkopf; PMLR 32(2):478-486

Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm

Alexander Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun; PMLR 32(2):487-495

Linear Programming for Large-Scale Markov Decision Problems

Alan Malek, Yasin Abbasi-Yadkori, Peter Bartlett; PMLR 32(2):496-504

Linear Time Solver for Primal SVM

Feiping Nie, Yizhen Huang, Heng Huang; PMLR 32(2):505-513

Memory (and Time) Efficient Sequential Monte Carlo

Seong-Hwan Jun, Alexandre Bouchard-Côté; PMLR 32(2):514-522

Scaling SVM and Least Absolute Deviations via Exact Data Reduction

Jie Wang, Peter Wonka, Jieping Ye; PMLR 32(2):523-531

Latent Semantic Representation Learning for Scene Classification

Xin Li, Yuhong Guo; PMLR 32(2):532-540

Least Squares Revisited: Scalable Approaches for Multi-class Prediction

Alekh Agarwal, Sham Kakade, Nikos Karampatziakis, Le Song, Gregory Valiant; PMLR 32(2):541-549

Local algorithms for interactive clustering

Pranjal Awasthi, Maria Balcan, Konstantin Voevodski; PMLR 32(2):550-558

Model-Based Relational RL When Object Existence is Partially Observable

Ngo Ahn Vien, Marc Toussaint; PMLR 32(2):559-567

A new Q(lambda) with interim forward view and Monte Carlo equivalence

Rich Sutton, Ashique Rupam Mahmood, Doina Precup, Hado Hasselt; PMLR 32(2):568-576

On Robustness and Regularization of Structural Support Vector Machines

Mohamad Ali Torkamani, Daniel Lowd; PMLR 32(2):577-585

Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting

Oscar Beijbom, Mohammad Saberian, David Kriegman, Nuno Vasconcelos; PMLR 32(2):586-594

Multimodal Neural Language Models

Ryan Kiros, Ruslan Salakhutdinov, Rich Zemel; PMLR 32(2):595-603

Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods

Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli; PMLR 32(2):604-612

Alternating Minimization for Mixed Linear Regression

Xinyang Yi, Constantine Caramanis, Sujay Sanghavi; PMLR 32(2):613-621

Stochastic Neighbor Compression

Matt Kusner, Stephen Tyree, Kilian Weinberger, Kunal Agrawal; PMLR 32(2):622-630

Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification

Junfeng Wen, Chun-Nam Yu, Russell Greiner; PMLR 32(2):631-639

Nonparametric Estimation of Multi-View Latent Variable Models

Le Song, Animashree Anandkumar, Bo Dai, Bo Xie; PMLR 32(2):640-648

Structured Generative Models of Natural Source Code

Chris Maddison, Daniel Tarlow; PMLR 32(2):649-657

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data

Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain; PMLR 32(2):658-666

Statistical analysis of stochastic gradient methods for generalized linear models

Panagiotis Toulis, Edoardo Airoldi, Jason Rennie; PMLR 32(2):667-675

Coding for Random Projections

Ping Li, Michael Mitzenmacher, Anshumali Shrivastava; PMLR 32(2):676-684

Fast Computation of Wasserstein Barycenters

Marco Cuturi, Arnaud Doucet; PMLR 32(2):685-693

Global graph kernels using geometric embeddings

Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Chiranjib Bhattacharyya; PMLR 32(2):694-702

Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data

Zhiyuan Chen, Bing Liu; PMLR 32(2):703-711

K-means recovers ICA filters when independent components are sparse

Alon Vinnikov, Shai Shalev-Shwartz; PMLR 32(2):712-720

Learning Mixtures of Linear Classifiers

Yuekai Sun, Stratis Ioannidis, Andrea Montanari; PMLR 32(2):721-729

The Falling Factorial Basis and Its Statistical Applications

Yu-Xiang Wang, Alex Smola, Ryan Tibshirani; PMLR 32(2):730-738

Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes

Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet, Mohan Kankanhalli; PMLR 32(2):739-747

A Unifying View of Representer Theorems

Andreas Argyriou, Francesco Dinuzzo; PMLR 32(2):748-756

Online Clustering of Bandits

Claudio Gentile, Shuai Li, Giovanni Zappella; PMLR 32(2):757-765

Cold-start Active Learning with Robust Ordinal Matrix Factorization

Neil Houlsby, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani; PMLR 32(2):766-774

Multivariate Maximal Correlation Analysis

Hoang Vu Nguyen, Emmanuel Müller, Jilles Vreeken, Pavel Efros, Klemens Böhm; PMLR 32(2):775-783

Efficient Label Propagation

Yasuhiro Fujiwara, Go Irie; PMLR 32(2):784-792

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm

Hadi Daneshmand, Manuel Gomez-Rodriguez, Le Song, Bernhard Schoelkopf; PMLR 32(2):793-801

Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising

Ling Yan, Wu-Jun Li, Gui-Rong Xue, Dingyi Han; PMLR 32(2):802-810

Putting MRFs on a Tensor Train

Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry Vetrov; PMLR 32(2):811-819

Efficient Algorithms for Robust One-bit Compressive Sensing

Lijun Zhang, Jinfeng Yi, Rong Jin; PMLR 32(2):820-828

Learning Complex Neural Network Policies with Trajectory Optimization

Sergey Levine, Vladlen Koltun; PMLR 32(2):829-837

Composite Quantization for Approximate Nearest Neighbor Search

Ting Zhang, Chao Du, Jingdong Wang; PMLR 32(2):838-846

Local Ordinal Embedding

Yoshikazu Terada, Ulrike Luxburg; PMLR 32(2):847-855

Reducing Dueling Bandits to Cardinal Bandits

Nir Ailon, Zohar Karnin, Thorsten Joachims; PMLR 32(2):856-864

Large-margin Weakly Supervised Dimensionality Reduction

Chang Xu, Dacheng Tao, Chao Xu, Yong Rui; PMLR 32(2):865-873

Joint Inference of Multiple Label Types in Large Networks

Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang, Sofus Macskassy; PMLR 32(2):874-882

Hard-Margin Active Linear Regression

Elad Hazan, Zohar Karnin; PMLR 32(2):883-891

Maximum Margin Multiclass Nearest Neighbors

Aryeh Kontorovich, Roi Weiss; PMLR 32(2):892-900

Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications

Tian Lin, Bruno Abrahao, Robert Kleinberg, John Lui, Wei Chen; PMLR 32(2):901-909

Sparse meta-Gaussian information bottleneck

Melani Rey, Volker Roth, Thomas Fuchs; PMLR 32(2):910-918

Nonparametric Estimation of Renyi Divergence and Friends

Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, Larry Wasserman; PMLR 32(2):919-927

Robust Inverse Covariance Estimation under Noisy Measurements

Jun-Kun Wang, Shou-de Lin; PMLR 32(2):928-936

Bayesian Optimization with Inequality Constraints

Jacob Gardner, Matt Kusner,  Zhixiang, Kilian Weinberger, John Cunningham; PMLR 32(2):937-945

Circulant Binary Embedding

Felix Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang; PMLR 32(2):946-954

Multiple Testing under Dependence via Semiparametric Graphical Models

Jie Liu, Chunming Zhang, Elizabeth Burnside, David Page; PMLR 32(2):955-963

Making Fisher Discriminant Analysis Scalable

Bojun Tu, Zhihua Zhang, Shusen Wang, Hui Qian; PMLR 32(2):964-972

Hierarchical Dirichlet Scaling Process

Dongwoo Kim, Alice Oh; PMLR 32(2):973-981

Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process

Issei Sato, Hiroshi Nakagawa; PMLR 32(2):982-990

A PAC-Bayesian bound for Lifelong Learning

Anastasia Pentina, Christoph Lampert; PMLR 32(2):991-999

Communication-Efficient Distributed Optimization using an Approximate Newton-type Method

Ohad Shamir, Nati Srebro, Tong Zhang; PMLR 32(2):1000-1008

Concept Drift Detection Through Resampling

Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer; PMLR 32(2):1009-1017

Anti-differentiating approximation algorithms:A case study with min-cuts, spectral, and flow

David Gleich, Michael Mahoney; PMLR 32(2):1018-1025

A Bayesian Wilcoxon signed-rank test based on the Dirichlet process

Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon, Fabrizio Ruggeri; PMLR 32(2):1026-1034

Min-Max Problems on Factor Graphs

Siamak Ravanbakhsh, Christopher Srinivasa, Brendan Frey, Russell Greiner; PMLR 32(2):1035-1043

Distributed Stochastic Gradient MCMC

Sungjin Ahn, Babak Shahbaba, Max Welling; PMLR 32(2):1044-1052

Nearest Neighbors Using Compact Sparse Codes

Anoop Cherian; PMLR 32(2):1053-1061

Optimal Mean Robust Principal Component Analysis

Feiping Nie, Jianjun Yuan, Heng Huang; PMLR 32(2):1062-1070

Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows

Robert Busa-Fekete, Eyke Huellermeier, Balázs Szörényi; PMLR 32(2):1071-1079

Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations

Bilal Ahmed, Thomas Thesen, Karen Blackmon, Yijun Zhao, Orrin Devinsky, Ruben Kuzniecky, Carla Brodley; PMLR 32(2):1080-1088

A Physics-Based Model Prior for Object-Oriented MDPs

Jonathan Scholz, Martin Levihn, Charles Isbell, David Wingate; PMLR 32(2):1089-1097

Outlier Path: A Homotopy Algorithm for Robust SVM

Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Ichiro Takeuchi; PMLR 32(2):1098-1106

Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data

Naiyan Wang, Dit-Yan Yeung; PMLR 32(2):1107-1115

Latent Confusion Analysis by Normalized Gamma Construction

Issei Sato, Hisashi Kashima, Hiroshi Nakagawa; PMLR 32(2):1116-1124

Finito: A faster, permutable incremental gradient method for big data problems

Aaron Defazio, Justin Domke,  Caetano; PMLR 32(2):1125-1133

Ensemble Methods for Structured Prediction

Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri; PMLR 32(2):1134-1142

Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance

Simone Romano, James Bailey, Vinh Nguyen, Karin Verspoor; PMLR 32(2):1143-1151

Preserving Modes and Messages via Diverse Particle Selection

Jason Pacheco, Silvia Zuffi, Michael Black, Erik Sudderth; PMLR 32(2):1152-1160

Nonlinear Information-Theoretic Compressive Measurement Design

Liming Wang, Abolfazl Razi, Miguel Rodrigues, Robert Calderbank, Lawrence Carin; PMLR 32(2):1161-1169

Dual Query: Practical Private Query Release for High Dimensional Data

Marco Gaboardi, Emilio Jesus Gallego Arias, Justin Hsu, Aaron Roth, Zhiwei Steven Wu; PMLR 32(2):1170-1178

Deep Boosting

Corinna Cortes, Mehryar Mohri, Umar Syed; PMLR 32(2):1179-1187

Distributed Representations of Sentences and Documents

Quoc Le, Tomas Mikolov; PMLR 32(2):1188-1196

Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models

Robert McGibbon, Bharath Ramsundar, Mohammad Sultan, Gert Kiss, Vijay Pande; PMLR 32(2):1197-1205

Online Multi-Task Learning for Policy Gradient Methods

Haitham Bou Ammar, Eric Eaton, Paul Ruvolo, Matthew Taylor; PMLR 32(2):1206-1214

Affinity Weighted Embedding

Jason Weston, Ron Weiss, Hector Yee; PMLR 32(2):1215-1223

Learning the Parameters of Determinantal Point Process Kernels

Raja Hafiz Affandi, Emily Fox, Ryan Adams, Ben Taskar; PMLR 32(2):1224-1232

Discrete Chebyshev Classifiers

Elad Eban, Elad Mezuman, Amir Globerson; PMLR 32(2):1233-1241

Deep AutoRegressive Networks

Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra; PMLR 32(2):1242-1250

A Convergence Rate Analysis for LogitBoost, MART and Their Variant

Peng Sun, Tong Zhang, Jie Zhou; PMLR 32(2):1251-1259

Inferning with High Girth Graphical Models

Uri Heinemann, Amir Globerson; PMLR 32(2):1260-1268

Learning Latent Variable Gaussian Graphical Models

Zhaoshi Meng, Brian Eriksson, Al Hero; PMLR 32(2):1269-1277

Stochastic Backpropagation and Approximate Inference in Deep Generative Models

Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra; PMLR 32(2):1278-1286

One Practical Algorithm for Both Stochastic and Adversarial Bandits

Yevgeny Seldin, Aleksandrs Slivkins; PMLR 32(2):1287-1295

Robust and Efficient Kernel Hyperparameter Paths with Guarantees

Joachim Giesen, Soeren Laue, Patrick Wieschollek; PMLR 32(2):1296-1304

Active Transfer Learning under Model Shift

Xuezhi Wang, Tzu-Kuo Huang, Jeff Schneider; PMLR 32(2):1305-1313

Approximate Policy Iteration Schemes: A Comparison

Bruno Scherrer; PMLR 32(2):1314-1322

Stable and Efficient Representation Learning with Nonnegativity Constraints

Tsung-Han Lin, H. T. Kung; PMLR 32(2):1323-1331

Sample Efficient Reinforcement Learning with Gaussian Processes

Robert Grande, Thomas Walsh, Jonathan How; PMLR 32(2):1332-1340

Memory and Computation Efficient PCA via Very Sparse Random Projections

Farhad Pourkamali Anaraki, Shannon Hughes; PMLR 32(2):1341-1349

Time-Regularized Interrupting Options (TRIO)

Timothy Mann, Daniel Mankowitz, Shie Mannor; PMLR 32(2):1350-1358

Randomized Nonlinear Component Analysis

David Lopez-Paz, Suvrit Sra, Alex Smola, Zoubin Ghahramani, Bernhard Schoelkopf; PMLR 32(2):1359-1367

High Order Regularization for Semi-Supervised Learning of Structured Output Problems

Yujia Li, Rich Zemel; PMLR 32(2):1368-1376

Transductive Learning with Multi-class Volume Approximation

Gang Niu, Bo Dai, Christoffel Plessis, Masashi Sugiyama; PMLR 32(2):1377-1385

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison

Borja Balle, William Hamilton, Joelle Pineau; PMLR 32(2):1386-1394

Effective Bayesian Modeling of Groups of Related Count Time Series

Nicolas Chapados; PMLR 32(2):1395-1403

Variational Inference for Sequential Distance Dependent Chinese Restaurant Process

Sergey Bartunov, Dmitry Vetrov; PMLR 32(2):1404-1412

Discovering Latent Network Structure in Point Process Data

Scott Linderman, Ryan Adams; PMLR 32(2):1413-1421

A Kernel Independence Test for Random Processes

Kacper Chwialkowski, Arthur Gretton; PMLR 32(2):1422-1430

Learning to Disentangle Factors of Variation with Manifold Interaction

Scott Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee; PMLR 32(2):1431-1439

Learning Modular Structures from Network Data and Node Variables

Elham Azizi, Edoardo Airoldi, James Galagan; PMLR 32(2):1440-1448

Probabilistic Partial Canonical Correlation Analysis

Yusuke Mukuta,  Harada; PMLR 32(2):1449-1457

Skip Context Tree Switching

Marc Bellemare, Joel Veness, Erik Talvitie; PMLR 32(2):1458-1466

Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians

Christopher Tosh, Sanjoy Dasgupta; PMLR 32(2):1467-1475

Marginalized Denoising Auto-encoders for Nonlinear Representations

Minmin Chen, Kilian Weinberger, Fei Sha, Yoshua Bengio; PMLR 32(2):1476-1484

Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations

David Barber, Yali Wang; PMLR 32(2):1485-1493

Fast Multi-stage Submodular Maximization

Kai Wei, Rishabh Iyer, Jeff Bilmes; PMLR 32(2):1494-1502

Programming by Feedback

Marc Schoenauer, Riad Akrour, Michele Sebag, Jean-Christophe Souplet; PMLR 32(2):1503-1511

Probabilistic Matrix Factorization with Non-random Missing Data

Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani; PMLR 32(2):1512-1520

Pursuit-Evasion Without Regret, with an Application to Trading

Lili Dworkin, Michael Kearns, Yuriy Nevmyvaka; PMLR 32(2):1521-1529

The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation

Sven Kurras, Ulrike Luxburg, Gilles Blanchard; PMLR 32(2):1530-1538

Riemannian Pursuit for Big Matrix Recovery

Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken, Sinno Jialin Pan; PMLR 32(2):1539-1547

Dynamic Programming Boosting for Discriminative Macro-Action Discovery

Leonidas Lefakis, Francois Fleuret; PMLR 32(2):1548-1556

Online Stochastic Optimization under Correlated Bandit Feedback

Mohammad Gheshlaghi azar, Alessandro Lazaric, Emma Brunskill; PMLR 32(2):1557-1565

Weighted Graph Clustering with Non-Uniform Uncertainties

Yudong Chen, Shiau Hong Lim, Huan Xu; PMLR 32(2):1566-1574

GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results

Philip Thomas; PMLR 32(2):1575-1583

A Bayesian Framework for Online Classifier Ensemble

Qinxun Bai, Henry Lam, Stan Sclaroff; PMLR 32(2):1584-1592

Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm

Jacob Steinhardt, Percy Liang; PMLR 32(2):1593-1601

Gaussian Approximation of Collective Graphical Models

Liping Liu, Daniel Sheldon, Thomas Dietterich; PMLR 32(2):1602-1610

On learning to localize objects with minimal supervision

Hyun Oh Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell; PMLR 32(2):1611-1619

Multiresolution Matrix Factorization

Risi Kondor, Nedelina Teneva, Vikas Garg; PMLR 32(2):1620-1628

Learnability of the Superset Label Learning Problem

Liping Liu, Thomas Dietterich; PMLR 32(2):1629-1637

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li, Robert Schapire; PMLR 32(2):1638-1646

Structured Recurrent Temporal Restricted Boltzmann Machines

Roni Mittelman, Benjamin Kuipers, Silvio Savarese, Honglak Lee; PMLR 32(2):1647-1655

Scalable and Robust Bayesian Inference via the Median Posterior

Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David Dunson; PMLR 32(2):1656-1664

Kernel Adaptive Metropolis-Hastings

Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton; PMLR 32(2):1665-1673

Input Warping for Bayesian Optimization of Non-Stationary Functions

Jasper Snoek, Kevin Swersky, Rich Zemel, Ryan Adams; PMLR 32(2):1674-1682

Stochastic Gradient Hamiltonian Monte Carlo

Tianqi Chen, Emily Fox, Carlos Guestrin; PMLR 32(2):1683-1691

A Deep Semi-NMF Model for Learning Hidden Representations

George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou, Bjoern Schuller; PMLR 32(2):1692-1700

Asynchronous Distributed ADMM for Consensus Optimization

Ruiliang Zhang, James Kwok; PMLR 32(2):1701-1709

Spectral Regularization for Max-Margin Sequence Tagging

Ariadna Quattoni, Borja Balle, Xavier Carreras, Amir Globerson; PMLR 32(2):1710-1718

Learning by Stretching Deep Networks

Gaurav Pandey, Ambedkar Dukkipati; PMLR 32(2):1719-1727

Nonnegative Sparse PCA with Provable Guarantees

Megasthenis Asteris, Dimitris Papailiopoulos, Alexandros Dimakis; PMLR 32(2):1728-1736

Active Learning of Parameterized Skills

Bruno Da Silva, George Konidaris, Andrew Barto; PMLR 32(2):1737-1745

Learning Ordered Representations with Nested Dropout

Oren Rippel, Michael Gelbart, Ryan Adams; PMLR 32(2):1746-1754

Learning the Irreducible Representations of Commutative Lie Groups

Taco Cohen, Max Welling; PMLR 32(2):1755-1763

Towards End-To-End Speech Recognition with Recurrent Neural Networks

Alex Graves, Navdeep Jaitly; PMLR 32(2):1764-1772

Multi-period Trading Prediction Markets with Connections to Machine Learning

Jinli Hu, Amos Storkey; PMLR 32(2):1773-1781

Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets

Diederik Kingma, Max Welling; PMLR 32(2):1782-1790

Neural Variational Inference and Learning in Belief Networks

Andriy Mnih, Karol Gregor; PMLR 32(2):1791-1799

Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors

Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David Dunson, Lawrence Carin; PMLR 32(2):1800-1808

Beta Diffusion Trees

Creighton Heaukulani, David Knowles, Zoubin Ghahramani; PMLR 32(2):1809-1817

Learning Character-level Representations for Part-of-Speech Tagging

Cicero Dos Santos, Bianca Zadrozny; PMLR 32(2):1818-1826

Saddle Points and Accelerated Perceptron Algorithms

Adams Wei Yu, Fatma Kilinc-Karzan, Jaime Carbonell; PMLR 32(2):1827-1835

Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization

Hua Wang, Feiping Nie, Heng Huang; PMLR 32(2):1836-1844

Learning from Contagion (Without Timestamps)

Kareem Amin, Hoda Heidari, Michael Kearns; PMLR 32(2):1845-1853

Stochastic Variational Inference for Bayesian Time Series Models

Matthew Johnson, Alan Willsky; PMLR 32(2):1854-1862

A Clockwork RNN

Jan Koutnik, Klaus Greff, Faustino Gomez, Juergen Schmidhuber; PMLR 32(2):1863-1871

Estimating Latent-Variable Graphical Models using Moments and Likelihoods

Arun Tejasvi Chaganty, Percy Liang; PMLR 32(2):1872-1880

Universal Matrix Completion

Srinadh Bhojanapalli, Prateek Jain; PMLR 32(2):1881-1889

Finding Dense Subgraphs via Low-Rank Bilinear Optimization

Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis, Constantine Caramanis; PMLR 32(2):1890-1898

Compositional Morphology for Word Representations and Language Modelling

Jan Botha, Phil Blunsom; PMLR 32(2):1899-1907

Learning Polynomials with Neural Networks

Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang; PMLR 32(2):1908-1916

Exponential Family Matrix Completion under Structural Constraints

Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh; PMLR 32(2):1917-1925

Sample-based approximate regularization

Philip Bachman, Amir-Massoud Farahmand, Doina Precup; PMLR 32(2):1926-1934

A Compilation Target for Probabilistic Programming Languages

Brooks Paige, Frank Wood; PMLR 32(2):1935-1943

Adaptive Monte Carlo via Bandit Allocation

James Neufeld, Andras Gyorgy, Csaba Szepesvari, Dale Schuurmans; PMLR 32(2):1944-1952

Efficient Dimensionality Reduction for High-Dimensional Network Estimation

Safiye Celik, Benjamin Logsdon, Su-In Lee; PMLR 32(2):1953-1961

Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes

E. Busra Celikkaya, Christian Shelton; PMLR 32(2):1962-1970

Doubly Stochastic Variational Bayes for non-Conjugate Inference

Michalis Titsias, Miguel Lázaro-Gredilla; PMLR 32(2):1971-1979

Efficient Learning of Mahalanobis Metrics for Ranking

Daryl Lim, Gert Lanckriet; PMLR 32(2):1980-1988

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare

Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal; PMLR 32(2):1989-1997

A reversible infinite HMM using normalised random measures

David Knowles, Zoubin Ghahramani, Konstantina Palla; PMLR 32(2):1998-2006

Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing

Benjamin Haeffele, Eric Young, Rene Vidal; PMLR 32(2):2007-2015

Influence Function Learning in Information Diffusion Networks

Nan Du, Yingyu Liang, Maria Balcan, Le Song; PMLR 32(2):2016-2024

subscribe via RSS