Papers
Bayesian Logistic Gaussian Process Models for Dynamic Networks
Daniele Durante, David Dunson
Approximate Slice Sampling for Bayesian Posterior Inference
Christopher DuBois, Anoop Korattikara, Max Welling et al.
Pan-sharpening with a Bayesian nonparametric dictionary learning model
Xinghao Ding, Yiyong Jiang, Yue Huang et al.
Efficient Distributed Topic Modeling with Provable Guarantees
Weicong Ding, Mohammad Rohban, Prakash Ishwar et al.
Sparsity and the Truncated l^2-norm
Lee Dicker
Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus
Vinny Davies, Richard Reeve, William Harvey et al.
Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems
Robert Cohn, Satinder Singh, Edmund Durfee
Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs
Jianhui Chen, Tianbao Yang, Shenghuo Zhu
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.