Preface

Dinh Phung, Hang Li; PMLR 39:i-xiv

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Theoretical Analyses on Ensemble and Multiple Kernel Regressors

Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo; PMLR 39:1-15

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Sparsity on Statistical Simplexes and Diversity in Social Ranking

Ke Sun, Hisham Mohamed, Stephane Marchand-Maillet; PMLR 39:16-31

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Support vector machines with indefinite kernels

Ibrahim Alabdulmohsin, Xin Gao, Xiangliang Zhang Zhang; PMLR 39:32-47

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Efficient Sample Mining for Object Detection

Olivier Canevet, Francois Fleuret; PMLR 39:48-63

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Sample Distillation for Object Detection and Image Classification

Olivier Canevet, Leonidas Lefakis, Francois Fleuret; PMLR 39:64-79

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Dual online inference for latent Dirichlet allocation

Khoat Than, Tung Doan; PMLR 39:80-95

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Structured Denoising Autoencoder for Fault Detection and Analysis

Takaaki Tagawa, Yukihiro Tadokoro, Takehisa Yairi; PMLR 39:96-111

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Polya-gamma augmentations for factor models

Arto Klami; PMLR 39:112-128

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A Fast Hierarchical Alternating Least Squares Algorithm for Orthogonal Nonnegative Matrix Factorization

Keigo Kimura, Yuzuru Tanaka, Mineichi Kudo; PMLR 39:129-141

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Bibliographic Analysis with the Citation Network Topic Model

Kar Wai Lim, Wray Buntine; PMLR 39:142-158

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Quasi Newton Temporal Difference Learning

Arash Givchi, Maziar Palhang; PMLR 39:159-172

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Sparse binary zero-sum games

David Auger, Jianlin Liu, Sylkvie Ruette, David Saint-Pierre, Oliver Teytaud; PMLR 39:173-188

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Interval Insensitive Loss for Ordinal Classification

Kostiantyn Antoniuk, Vojtech Franc, Vaclav Hlavac; PMLR 39:189-204

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Towards Maximum Likelihood: Learning Undirected Graphical Models using Persistent Sequential Monte Carlo

Hanchen Xiong, Sandor Szedmak, Justus Piater; PMLR 39:205-220

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Nonlinear Dimensionality Reduction of Data by Deep Distributed Random Samplings

Xiao-Lei Zhang; PMLR 39:221-233

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Learning with Augmented Multi-Instance View

Yue Zhu, Jianxin Wu, Yuan Jiang, Zhi-Hua Zhou; PMLR 39:234-249

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Online matrix prediction for sparse loss matrices

Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto, Koji Tsuda; PMLR 39:250-265

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Online Passive Aggressive Active Learning and Its Applications

Jing Lu, Peilin Zhao, Steven Hoi; PMLR 39:266-282

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Ordinal Random Fields for Recommender Systems

Shaowu Liu, Truyen Tran, Gang Li; PMLR 39:283-298

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Reinforcement learning with value advice

Mayank Daswani, Peter Sunehag, Marcus Hutter; PMLR 39:299-314

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A UCB-Like Strategy of Collaborative Filtering

Atsuyoshi Nakamura; PMLR 39:315-329

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Variational Gaussian Inference for Bilinear Models of Count Data

Young-Jun Ko, Mohammad Khan; PMLR 39:330-343

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Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions

Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu; PMLR 39:344-359

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Ensembles for Time Series Forecasting

Mariana Oliveira, Luis Torgo; PMLR 39:360-370

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Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification

Hsuan-Tien Lin; PMLR 39:371-386

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