Papers
Two-Layer Multiple Kernel Learning
Jinfeng Zhuang, Ivor W. Tsang, Steven C.H. Hoi
Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning
Xueyuan Zhou, Nathan Srebro
Semi-supervised Learning by Higher Order Regularization
Xueyuan Zhou, Mikhail Belkin
Dependent Hierarchical Beta Process for Image Interpolation and Denoising
Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro et al.
Multi-Label Output Codes using Canonical Correlation Analysis
Yi Zhang, Jeff Schneider
Generalization Bound for Infinitely Divisible Empirical Process
Chao Zhang, Dacheng Tao
An Instantiation-Based Theorem Prover for First-Order Programming
Erik Zawadzki, Geoffrey Gordon, Andre Platzer
A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems
Xiao–Tong Yuan, Shuicheng Yan
Efficient variable selection in support vector machines via the alternating direction method of multipliers
Gui–Bo Ye, Yifei Chen, Xiaohui Xie
Bridging the Language Gap: Topic Adaptation for Documents with Different Technicality
Shuang–Hong Yang, Steven P. Crain, Hongyuan Zha
The Sample Complexity of Self-Verifying Bayesian Active Learning
Liu Yang, Steve Hanneke, Jaime Carbonell
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