Papers
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication
Peng Jiang, Gagan Agrawal
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs
Han Shao, Xiaotian Yu, Irwin King et al.
Alternating optimization of decision trees, with application to learning sparse oblique trees
Miguel A. Carreira-Perpinan, Pooya Tavallali
A Lyapunov-based Approach to Safe Reinforcement Learning
Yinlam Chow, Ofir Nachum, Edgar Duenez-Guzman et al.
A Mathematical Model For Optimal Decisions In A Representative Democracy
Malik Magdon-Ismail, Lirong Xia
A Model for Learned Bloom Filters and Optimizing by Sandwiching
Michael Mitzenmacher
Amortized Inference Regularization
Rui Shu, Hung H Bui, Shengjia Zhao et al.
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems
Yair Carmon, John C. Duchi
A Neural Compositional Paradigm for Image Captioning
Bo Dai, Sanja Fidler, Dahua Lin
An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression
Sheng Chen, Arindam Banerjee
An Information-Theoretic Analysis for Thompson Sampling with Many Actions
Shi Dong, Benjamin Van Roy
An intriguing failing of convolutional neural networks and the CoordConv solution
Rosanne Liu, Joel Lehman, Piero Molino et al.
An Off-policy Policy Gradient Theorem Using Emphatic Weightings
Ehsan Imani, Eric Graves, Martha White
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch, Kalina Jasinska, Mikhail Kuznetsov et al.
Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog
Sang-Woo Lee, Yu-Jung Heo, Byoung-Tak Zhang
Approximate Knowledge Compilation by Online Collapsed Importance Sampling
Tal Friedman, Guy Van den Broeck
Approximating Real-Time Recurrent Learning with Random Kronecker Factors
Asier Mujika, Florian Meier, Angelika Steger
Approximation algorithms for stochastic clustering
David Harris, Shi Li, Aravind Srinivasan et al.
A Practical Algorithm for Distributed Clustering and Outlier Detection
Jiecao Chen, Erfan Sadeqi Azer, Qin Zhang
A probabilistic population code based on neural samples
Sabyasachi Shivkumar, Richard Lange, Ankani Chattoraj et al.
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon Kohl, Bernardino Romera-Paredes, Clemens Meyer et al.
A Reduction for Efficient LDA Topic Reconstruction
Matteo Almanza, Flavio Chierichetti, Alessandro Panconesi et al.