Papers
Classification with Incomplete Data Using Dirichlet Process Priors
Chunping Wang, Xuejun Liao, Lawrence Carin et al.
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Antti Honkela, Tapani Raiko, Mikael Kuusela et al.
A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification
Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh et al.
A Generalized Path Integral Control Approach to Reinforcement Learning
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials
Rahul Gupta, Sunita Sarawagi, Ajit A. Diwan
Inducing Tree-Substitution Grammars
Trevor Cohn, Phil Blunsom, Sharon Goldwater
Covariance in Unsupervised Learning of Probabilistic Grammars
Shay B. Cohen, Noah A. Smith
Gaussian Processes for Machine Learning (GPML) Toolbox
Carl Edward Rasmussen, Hannes Nickisch
Semi-Supervised Novelty Detection
Gilles Blanchard, Gyemin Lee, Clayton Scott
Tree Decomposition for Large-Scale SVM Problems
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin et al.
Linear Algorithms for Online Multitask Classification
Giovanni Cavallanti, Nicoló Cesa-Bianchi, Claudio Gentile
Expectation Truncation and the Benefits of Preselection In Training Generative Models
Jörg Lücke, Julian Eggert
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
Nguyen Xuan Vinh, Julien Epps, James Bailey
Regret Bounds and Minimax Policies under Partial Monitoring
Jean-Yves Audibert, Sébastien Bubeck
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Ido Cohn, Tal El-Hay, Nir Friedman et al.
Using Contextual Representations to Efficiently Learn Context-Free Languages
Alexander Clark, Rémi Eyraud, Amaury Habrard
Topology Selection in Graphical Models of Autoregressive Processes
Jitkomut Songsiri, Lieven Vandenberghe
Learnability, Stability and Uniform Convergence
Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro et al.
Stochastic Composite Likelihood
Joshua V. Dillon, Guy Lebanon
WEKA−Experiences with a Java Open-Source Project
Remco R. Bouckaert, Eibe Frank, Mark A. Hall et al.
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
Miloš Radovanović
Rademacher Complexities and Bounding the Excess Risk in Active Learning
Vladimir Koltchinskii
Sparse Semi-supervised Learning Using Conjugate Functions
Shiliang Sun, John Shawe-Taylor
Composite Binary Losses
Mark D. Reid, Robert C. Williamson