Papers
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation
Sven Kurras, Ulrike Luxburg, Gilles Blanchard
Pursuit-Evasion Without Regret, with an Application to Trading
Lili Dworkin, Michael Kearns, Yuriy Nevmyvaka
Probabilistic Matrix Factorization with Non-random Missing Data
Jose Miguel Hernandez-Lobato, Neil Houlsby, Zoubin Ghahramani
Programming by Feedback
Marc Schoenauer, Riad Akrour, Michele Sebag et al.
Fast Multi-stage Submodular Maximization
Kai Wei, Rishabh Iyer, Jeff Bilmes
Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations
David Barber, Yali Wang
Marginalized Denoising Auto-encoders for Nonlinear Representations
Minmin Chen, Kilian Weinberger, Fei Sha et al.
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians
Christopher Tosh, Sanjoy Dasgupta
Skip Context Tree Switching
Marc Bellemare, Joel Veness, Erik Talvitie
Probabilistic Partial Canonical Correlation Analysis
Yusuke Mukuta, Harada
Learning Modular Structures from Network Data and Node Variables
Elham Azizi, Edoardo Airoldi, James Galagan
Learning to Disentangle Factors of Variation with Manifold Interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang et al.
A Kernel Independence Test for Random Processes
Kacper Chwialkowski, Arthur Gretton
Discovering Latent Network Structure in Point Process Data
Scott Linderman, Ryan Adams
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process
Sergey Bartunov, Dmitry Vetrov
Effective Bayesian Modeling of Groups of Related Count Time Series
Nicolas Chapados
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison
Borja Balle, William Hamilton, Joelle Pineau
Transductive Learning with Multi-class Volume Approximation
Gang Niu, Bo Dai, Christoffel Plessis et al.
High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li, Rich Zemel
Randomized Nonlinear Component Analysis
David Lopez-Paz, Suvrit Sra, Alex Smola et al.
Time-Regularized Interrupting Options (TRIO)
Timothy Mann, Daniel Mankowitz, Shie Mannor
Memory and Computation Efficient PCA via Very Sparse Random Projections
Farhad Pourkamali Anaraki, Shannon Hughes
Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh, Jonathan How
Stable and Efficient Representation Learning with Nonnegativity Constraints
Tsung-Han Lin, H. T. Kung
Approximate Policy Iteration Schemes: A Comparison
Bruno Scherrer