Papers
Learning with a Wasserstein Loss
Charlie Frogner, Chiyuan Zhang, Hossein Mobahi et al.
Large-scale probabilistic predictors with and without guarantees of validity
Vladimir Vovk, Ivan Petej, Valentina Fedorova
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation
Alaa Saade, Florent Krzakala, Lenka Zdeborová
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks
Minhyung Cho, Chandra Dhir, Jaehyung Lee
Texture Synthesis Using Convolutional Neural Networks
Leon Gatys, Alexander S Ecker, Matthias Bethge
Efficient Output Kernel Learning for Multiple Tasks
Pratik Kumar Jawanpuria, Maksim Lapin, Matthias Hein et al.
Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression
Yu-Ying Liu, Shuang Li, Fuxin Li et al.
Saliency, Scale and Information: Towards a Unifying Theory
Shafin Rahman, Neil Bruce
StopWasting My Gradients: Practical SVRG
Reza Babanezhad Harikandeh, Mohamed Osama Ahmed, Alim Virani et al.
Basis refinement strategies for linear value function approximation in MDPs
Gheorghe Comanici, Doina Precup, Prakash Panangaden
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference
Ted Meeds, Max Welling
Is Approval Voting Optimal Given Approval Votes?
Ariel D Procaccia, Nisarg Shah
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter, Jost Springenberg, Joschka Boedecker et al.
Secure Multi-party Differential Privacy
Peter Kairouz, Sewoong Oh, Pramod Viswanath
Expectation Particle Belief Propagation
Thibaut Lienart, Yee Whye Teh, Arnaud Doucet
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling
Ming Liang, Xiaolin Hu, Bo Zhang
Max-Margin Deep Generative Models
Chongxuan Li, Jun Zhu, Tianlin Shi et al.
Rethinking LDA: Moment Matching for Discrete ICA
Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien
Segregated Graphs and Marginals of Chain Graph Models
Ilya Shpitser
A Complete Recipe for Stochastic Gradient MCMC
Yi-An Ma, Tianqi Chen, Emily B. Fox
Supervised Learning for Dynamical System Learning
Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon
Neural Adaptive Sequential Monte Carlo
Shixiang (Shane) Gu, Zoubin Ghahramani, Richard E Turner
High-dimensional neural spike train analysis with generalized count linear dynamical systems
Yuanjun Gao, Lars Busing, Krishna V. Shenoy et al.