Papers
Random Bayesian networks with bounded indegree
Eunice Yuh-Jie Chen, Judea Pearl
PAC-Bayesian Theory for Transductive Learning
Luc Bégin, Pascal Germain, François Laviolette et al.
Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion
Mathieu Blondel, Yotaro Kubo, Ueda Naonori
Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability
Jeremias Berg, Matti Järvisalo, Brandon Malone
A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response
Ava Bargi, Richard Yi Xu, Zoubin Ghahramani et al.
A New Perspective on Learning Linear Separators with Large L_qL_p Margins
Maria-Florina Balcan, Christopher Berlind
Average Case Analysis of High-Dimensional Block-Sparse Recovery and Regression for Arbitrary Designs
Waheed Bajwa, Marco Duarte, Robert Calderbank
Hybrid Discriminative-Generative Approach with Gaussian Processes
Ricardo Andrade Pacheco, James Hensman, Max Zwiessele et al.
Information-Theoretic Characterization of Sparse Recovery
Cem Aksoylar, Venkatesh Saligrama
Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?
Shinichi Nakajima, Masashi Sugiyama
Distributed optimization of deeply nested systems
Miguel Carreira-Perpinan, Weiran Wang
Decontamination of Mutually Contaminated Models
Gilles Blanchard, Clayton Scott
Ensembles for Time Series Forecasting
Mariana Oliveira, Luis Torgo
Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions
Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang et al.
Variational Gaussian Inference for Bilinear Models of Count Data
Young-Jun Ko, Mohammad Khan
A UCB-Like Strategy of Collaborative Filtering
Atsuyoshi Nakamura
Reinforcement learning with value advice
Mayank Daswani, Peter Sunehag, Marcus Hutter
Ordinal Random Fields for Recommender Systems
Shaowu Liu, Truyen Tran, Gang Li
Online Passive Aggressive Active Learning and Its Applications
Jing Lu, Peilin Zhao, Steven Hoi
Online matrix prediction for sparse loss matrices
Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto et al.
Learning with Augmented Multi-Instance View
Yue Zhu, Jianxin Wu, Yuan Jiang et al.
Towards Maximum Likelihood: Learning Undirected Graphical Models using Persistent Sequential Monte Carlo
Hanchen Xiong, Sandor Szedmak, Justus Piater