Papers
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani, Yoav Freund
Online Prediction at the Limit of Zero Temperature
Mark Herbster, Stephen Pasteris, Shaona Ghosh
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing
Tom Goldstein, Min Li, Xiaoming Yuan
Distributionally Robust Logistic Regression
Soroosh Shafieezadeh-Abadeh, Peyman Mohajerin Esfahani, Daniel Huhn
Convergence Rates of Active Learning for Maximum Likelihood Estimation
Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli et al.
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors
Andrea Montanari, Daniel Reichman, Ofer Zeitouni
Bounding errors of Expectation-Propagation
Guillaume P Dehaene, Simon Barthelmé
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care
Sorathan Chaturapruek, John C. Duchi, Christopher Ré
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
Nihar Bhadresh Shah, Dengyong Zhou
Bidirectional Recurrent Neural Networks as Generative Models
Mathias Berglund, Tapani Raiko, Mikko Honkala et al.
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models
Theodoros Tsiligkaridis, Theodoros Tsiligkaridis, Keith Forsythe
Regret-Based Pruning in Extensive-Form Games
Noam Brown, Tuomas Sandholm
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution
Yan Huang, Wei Wang, Liang Wang
Robust PCA with compressed data
Wooseok Ha, Rina Foygel Barber
Distributed Submodular Cover: Succinctly Summarizing Massive Data
Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru et al.
A Universal Catalyst for First-Order Optimization
Hongzhou Lin, Julien Mairal, Zaid Harchaoui
Finite-Time Analysis of Projected Langevin Monte Carlo
Sebastien Bubeck, Ronen Eldan, Joseph Lehec
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction
Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama
On the Global Linear Convergence of Frank-Wolfe Optimization Variants
Simon Lacoste-Julien, Martin Jaggi
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
Rasmus Kyng, Anup Rao, Sushant Sachdeva
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma, Tim Salimans, Max Welling
Tractable Learning for Complex Probability Queries
Jessa Bekker, Jesse Davis, Arthur Choi et al.
Generalization in Adaptive Data Analysis and Holdout Reuse
Cynthia Dwork, Vitaly Feldman, Moritz Hardt et al.
Deep Knowledge Tracing
Chris Piech, Jonathan Bassen, Jonathan Huang et al.