Papers
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization
Niao He, Zaid Harchaoui
A Reduced-Dimension fMRI Shared Response Model
Po-Hsuan (Cameron) Chen, Janice Chen, Yaara Yeshurun et al.
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width
Christopher M De Sa, Ce Zhang, Kunle Olukotun et al.
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
Kevin Scaman, Rémi Lemonnier, Nicolas Vayatis
Alternating Minimization for Regression Problems with Vector-valued Outputs
Prateek Jain, Ambuj Tewari
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring
David Kappel, Stefan Habenschuss, Robert Legenstein et al.
Teaching Machines to Read and Comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette et al.
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen, Nan Ding, Lawrence Carin
Bayesian dark knowledge
Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy et al.
Learning both Weights and Connections for Efficient Neural Network
Song Han, Jeff Pool, John Tran et al.
Fast Rates for Exp-concave Empirical Risk Minimization
Tomer Koren, Kfir Levy
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
Rie Johnson, Tong Zhang
Black-box optimization of noisy functions with unknown smoothness
Jean-Bastien Grill, Michal Valko, Remi Munos et al.
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs
Wei Cao, Jian Li, Yufei Tao et al.
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily L Denton, Soumith Chintala, arthur szlam et al.
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.