Papers
On Multilabel Classification and Ranking with Bandit Feedback
Claudio Gentile, Francesco Orabona
Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity
Shay B. Cohen, Karl Stratos, Michael Collins et al.
Efficient State-Space Inference of Periodic Latent Force Models
Steven Reece, Siddhartha Ghosh, Alex Rogers et al.
Cover Tree Bayesian Reinforcement Learning
Nikolaos Tziortziotis, Christos Dimitrakakis, Konstantinos Blekas
A Tensor Approach to Learning Mixed Membership Community Models
Animashree Anandkumar, Rong Ge, Daniel Hsu et al.
Clustering Partially Observed Graphs via Convex Optimization
Yudong Chen, Ali Jalali, Sujay Sanghavi et al.
Ramp Loss Linear Programming Support Vector Machine
Xiaolin Huang, Lei Shi, Johan A.K. Suykens
Particle Gibbs with Ancestor Sampling
Fredrik Lindsten, Michael I. Jordan, Thomas B. Schön
Classifier Cascades and Trees for Minimizing Feature Evaluation Cost
Zhixiang (Eddie) Xu, Matt J. Kusner, Kilian Q. Weinberger et al.
Parallel MCMC with Generalized Elliptical Slice Sampling
Robert Nishihara, Iain Murray, Ryan P. Adams
The Student-t Mixture as a Natural Image Patch Prior with Application to Image Compression
Aäron van den Oord, Benjamin Schrauwen
pystruct - Learning Structured Prediction in Python
Andreas C. Müller, Sven Behnke
Causal Discovery with Continuous Additive Noise Models
Jonas Peters, Joris M. Mooij, Dominik Janzing et al.
Sparse Factor Analysis for Learning and Content Analytics
Andrew S. Lan, Andrew E. Waters, Christoph Studer et al.
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky et al.
Pattern Alternating Maximization Algorithm for Missing Data in High-Dimensional Problems
Nicolas Städler, Daniel J. Stekhoven, Peter Bühlmann
Expectation Propagation for Neural Networks with Sparsity-Promoting Priors
Pasi Jylänki, Aapo Nummenmaa, Aki Vehtari
Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs
Jun Zhu, Ning Chen, Eric P. Xing
Hitting and Commute Times in Large Random Neighborhood Graphs
Ulrike von Luxburg, Agnes Radl, Matthias Hein
Graph Estimation From Multi-Attribute Data
Mladen Kolar, Han Liu, Eric P. Xing
Adaptive Minimax Regression Estimation over Sparse ℓ_q-Hulls
Zhan Wang, Sandra Paterlini, Fuchang Gao et al.
Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife
Stefan Wager, Trevor Hastie, Bradley Efron
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
Matthew D. Hoffman, Andrew Gelman