Papers
Coherent Inference on Optimal Play in Game Trees
Philipp Hennig, David Stern, Thore Graepel
Collaborative Filtering on a Budget
Alexandros Karatzoglou, Alex Smola, Markus Weimer
Collaborative Filtering via Rating Concentration
Bert Huang, Tony Jebara
Combining Experiments to Discover Linear Cyclic Models with Latent Variables
Frederick Eberhardt, Patrik Hoyer, Richard Scheines
Conditional Density Estimation via Least-Squares Density Ratio Estimation
Masashi Sugiyama, Ichiro Takeuchi, Taiji Suzuki et al.
Contextual Multi-Armed Bandits
Tyler Lu, David Pal, Martin Pal
Convexity of Proper Composite Binary Losses
Mark Reid, Robert Williamson
Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials
Mark Schmidt, Kevin Murphy
Dense Message Passing for Sparse Principal Component Analysis
Kevin Sharp, Magnus Rattray
Dependent Indian Buffet Processes
Sinead Williamson, Peter Orbanz, Zoubin Ghahramani
Descent Methods for Tuning Parameter Refinement
Alexander Lorbert, Peter Ramadge
Detecting Weak but Hierarchically-Structured Patterns in Networks
Aarti Singh, Robert Nowak, Robert Calderbank
Deterministic Bayesian inference for the $p*$ model
Haakon Austad, Nial Friel
Dirichlet Process Mixtures of Generalized Linear Models
Lauren Hannah, David Blei, Warren Powell
Discriminative Topic Segmentation of Text and Speech
Mehryar Mohri, Pedro Moreno, Eugene Weinstein
Efficient Learning of Deep Boltzmann Machines
Ruslan Salakhutdinov, Hugo Larochelle
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Mauricio Álvarez, David Luengo, Michalis Titsias et al.
Efficient Reductions for Imitation Learning
Stephane Ross, Drew Bagnell
Elliptical slice sampling
Iain Murray, Ryan Adams, David MacKay
Empirical Bernstein Boosting
Pannagadatta Shivaswamy, Tony Jebara
Exclusive Lasso for Multi-task Feature Selection
Yang Zhou, Rong Jin, Steven Chu–Hong Hoi
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net
Alexander Lorbert, David Eis, Victoria Kostina et al.
Exploiting Feature Covariance in High-Dimensional Online Learning
Justin Ma, Alex Kulesza, Mark Dredze et al.
Exploiting Within-Clique Factorizations in Junction-Tree Algorithms
Julian McAuley, Tiberio Caetano
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Marc’Aurelio Ranzato, Alex Krizhevsky, Geoffrey Hinton