Papers
Cross-Domain Object Matching with Model Selection
Makoto Yamada, Masashi Sugiyama
Multicore Gibbs Sampling in Dense, Unstructured Graphs
Tianbing Xu, Alexander Ihler
Hierarchical Probabilistic Models for Group Anomaly Detection
Liang Xiong, Barnabás Póczos, Jeff Schneider et al.
Relational Learning with One Network: An Asymptotic Analysis
Rongjing Xiang, Jennifer Neville
Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation
David Wingate, Andreas Stuhlmueller, Noah Goodman
Information Theoretical Clustering via Semidefinite Programming
Meihong Wang, Fei Sha
Online Variational Inference for the Hierarchical Dirichlet Process
Chong Wang, John Paisley, David M. Blei
Active Boosted Learning (ActBoost)
Kirill Trapeznikov, Venkatesh Saligrama, David Castanon
Estimating Probabilities in Recommendation Systems
Mingxuan Sun, Guy Lebanon, Paul Kidwell
Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure
Veselin Stoyanov, Alexander Ropson, Jason Eisner
Machine Learning Markets
Amos Storkey
Kernel Belief Propagation
Le Song, Arthur Gretton, Danny Bickson et al.
Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities
Richard Socher, Andrew Maas, Christopher Manning
Assisting Main Task Learning by Heterogeneous Auxiliary Tasks with Applications to Skin Cancer Screening
Ning Situ, Xiaojing Yuan, George Zouridakis
Asymptotic Theory for Linear-Chain Conditional Random Fields
Mathieu Sinn, Pascal Poupart
Mixed Cumulative Distribution Networks
Ricardo Silva, Charles Blundell, Yee Whye Teh
Spectral Clustering on a Budget
Ohad Shamir, Naftali Tishby
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference
Matthias Seeger, Hannes Nickisch
Online Learning of Multiple Tasks and Their Relationships
Avishek Saha, Piyush Rai, Hal Daumé III et al.
Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback
Ankan Saha, Ambuj Tewari
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Stephane Ross, Geoffrey Gordon, Drew Bagnell
On NDCG Consistency of Listwise Ranking Methods
Pradeep Ravikumar, Ambuj Tewari, Eunho Yang
On the Estimation of α-Divergences
Barnabas Poczos, Jeff Schneider
Directional Statistics on Permutations
Sergey M. Plis, Stephen McCracken, Terran Lane et al.
Faithfulness in Chain Graphs: The Gaussian Case
Jose M. Peña