Papers
MCMC Methods for Bayesian Mixtures of Copulas
Ricardo Silva, Robert Gramacy
Locally Minimax Optimal Predictive Modeling with Bayesian Networks
Tomi Silander, Teemu Roos, Petri Myllymäki
Hash Kernels
Qinfeng Shi, James Petterson, Gideon Dror et al.
Efficient graphlet kernels for large graph comparison
Nino Shervashidze, SVN Vishwanathan, Tobias Petri et al.
PAC-Bayes Analysis Of Maximum Entropy Classification
John Shawe-Taylor, David Hardoon
PAC-Bayesian Generalization Bound for Density Estimation with Application to Co-clustering
Yevgeny Seldin, Naftali Tishby
Novelty detection: Unlabeled data definitely help
Clayton Scott, Gilles Blanchard
Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm
Mark Schmidt, Ewout Berg, Michael Friedlander et al.
Deep Boltzmann Machines
Ruslan Salakhutdinov, Geoffrey Hinton
Sequential Learning of Classifiers for Structured Prediction Problems
Dan Roth, Kevin Small, Ivan Titov
Learning the Switching Rate by Discretising Bernoulli Sources Online
Steven Rooij, Tim Erven
Inverse Optimal Heuristic Control for Imitation Learning
Nathan Ratliff, Brian Ziebart, Kevin Peterson et al.
Chromatic PAC-Bayes Bounds for Non-IID Data
Liva Ralaivola, Marie Szafranski, Guillaume Stempfel
Spanning Tree Approximations for Conditional Random Fields
Patrick Pletscher, Cheng Soon Ong, Joachim Buhmann
Exact and Approximate Sampling by Systematic Stochastic Search
Vikash Mansinghka, Daniel Roy, Eric Jonas et al.
Tractable Search for Learning Exponential Models of Rankings
Bhushan Mandhani, Marina Meila
Learning a Parametric Embedding by Preserving Local Structure
Laurens van der Maaten
Estimation Consistency of the Group Lasso and its Applications
Han Liu, Jian Zhang
A kernel method for unsupervised structured network inference
Christoph Lippert, Oliver Stegle, Zoubin Ghahramani et al.
Learning Sparse Markov Network Structure via Ensemble-of-Trees Models
Yuanqing Lin, Shenghuo Zhu, Daniel Lee et al.
Learning Exercise Policies for American Options
Yuxi Li, Csaba Szepesvari, Dale Schuurmans
Tighter and Convex Maximum Margin Clustering
Yu-Feng Li, Ivor W. Tsang, Jame Kwok et al.
Latent Wishart Processes for Relational Kernel Learning
Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung
Kernel Learning by Unconstrained Optimization
Fuxin Li, Yunshan Fu, Yu-Hong Dai et al.
Group Nonnegative Matrix Factorization for EEG Classification
Hyekyoung Lee, Seungjin Choi