Papers
Adaptive Exact Inference in Graphical Models
Özgür Sümer, Umut A. Acar, Alexander T. Ihler et al.
Unsupervised Supervised Learning II: Margin-Based Classification Without Labels
Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon
Efficient and Effective Visual Codebook Generation Using Additive Kernels
Jianxin Wu, Wei-Chian Tan, James M. Rehg
In All Likelihood, Deep Belief Is Not Enough
Lucas Theis, Sebastian Gerwinn, Fabian Sinz et al.
The Stationary Subspace Analysis Toolbox
Jan Saputra Müller, Paul von Bünau, Frank C. Meinecke et al.
Robust Approximate Bilinear Programming for Value Function Approximation
Marek Petrik, Shlomo Zilberstein
High-dimensional Covariance Estimation Based On Gaussian Graphical Models
Shuheng Zhou, Philipp Rütimann, Min Xu et al.
Hierarchical Knowledge Gradient for Sequential Sampling
Martijn R.K. Mes, Warren B. Powell, Peter I. Frazier
On Equivalence Relationships Between Classification and Ranking Algorithms
Şeyda Ertekin, Cynthia Rudin
Efficient Learning with Partially Observed Attributes
Nicoló Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir
Neyman-Pearson Classification, Convexity and Stochastic Constraints
Philippe Rigollet, Xin Tong
Scikit-learn: Machine Learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al.
Structured Variable Selection with Sparsity-Inducing Norms
Rodolphe Jenatton, Jean-Yves Audibert, Francis Bach
Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes
Elias Zavitsanos, Georgios Paliouras, George A. Vouros
Large Margin Hierarchical Classification with Mutually Exclusive Class Membership
Huixin Wang, Xiaotong Shen, Wei Pan
Convex and Network Flow Optimization for Structured Sparsity
Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski et al.
Bayesian Co-Training
Shipeng Yu, Balaji Krishnapuram, Rómer Rosales et al.
Theoretical Analysis of Bayesian Matrix Factorization
Shinichi Nakajima, Masashi Sugiyama
Kernel Analysis of Deep Networks
Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller
Weisfeiler-Lehman Graph Kernels
Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen et al.
Natural Language Processing (Almost) from Scratch
Ronan Collobert, Jason Weston, Léon Bottou et al.
LPmade: Link Prediction Made Easy
Ryan N. Lichtenwalter, Nitesh V. Chawla
Distance Dependent Chinese Restaurant Processes
David M. Blei, Peter I. Frazier
Parallel Algorithm for Learning Optimal Bayesian Network Structure
Yoshinori Tamada, Seiya Imoto, Satoru Miyano