Papers
High-Rank Matrix Completion
Brian Eriksson, Laura Balzano, Robert Nowak
Statistical test for consistent estimation of causal effects in linear non-Gaussian models
Doris Entner, Patrik Hoyer, Peter Spirtes
Copula Network Classifiers (CNCs)
Gal Elidan
Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space
Robert Durrant, Ata Kaban
Lifted coordinate descent for learning with trace-norm regularization
Miroslav Dudik, Zaid Harchaoui, Jerome Malick
Generic Methods for Optimization-Based Modeling
Justin Domke
A metric learning perspective of SVM: on the relation of LMNN and SVM
Huyen Do, Alexandros Kalousis, Jun Wang et al.
Deterministic Annealing for Semi-Supervised Structured Output Learning
Paramveer Dhillon, Sathiya Keerthi, Kedar Bellare et al.
There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems
Ofer Dekel, Ohad Shamir
Protocols for Learning Classifiers on Distributed Data
Hal Daume III, Jeff Phillips, Avishek Saha et al.
Hierarchical Relative Entropy Policy Search
Christian Daniel, Gerhard Neumann, Jan Peters
Wilks’ phenomenon and penalized likelihood-ratio test for nonparametric curve registration
Arnak Dalalyan, Olivier Collier
Gaussian Processes for time-marked time-series data
John Cunningham, Zoubin Ghahramani, Carl Rasmussen
Fast, Exact Model Selection and Permutation Testing for l2-Regularized Logistic Regression
Bryan Conroy, Paul Sajda
Minimax hypothesis testing for curve registration
Olivier Collier
Online Clustering with Experts
Anna Choromanska, Claire Monteleoni
Classifier Cascade for Minimizing Feature Evaluation Cost
Minmin Chen, Zhixiang Xu, Kilian Weinberger et al.
A Two-Graph Guided Multi-task Lasso Approach for eQTL Mapping
Xiaohui Chen, Xinghua Shi, Xing Xu et al.
Structured Sparse Canonical Correlation Analysis
Xi Chen, Liu Han, Jaime Carbonell
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit
Alexandra Carpentier, Remi Munos
Optimistic planning for Markov decision processes
Lucian Busoniu, Remi Munos
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
David Buchman, Mark Schmidt, Shakir Mohamed et al.
A Family of MCMC Methods on Implicitly Defined Manifolds
Marcus Brubaker, Mathieu Salzmann, Raquel Urtasun
Sample Complexity of Composite Likelihood
Joseph Bradley, Carlos Guestrin