Papers
NeuralFDR: Learning Discovery Thresholds from Hypothesis Features
Fei Xia, Martin J Zhang, James Y Zou et al.
Generating steganographic images via adversarial training
Jamie Hayes, George Danezis
The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities
Arun Suggala, Mladen Kolar, Pradeep K Ravikumar
Multi-way Interacting Regression via Factorization Machines
Mikhail Yurochkin, Xuanlong Nguyen, nikolaos Vasiloglou
Nonlinear Acceleration of Stochastic Algorithms
Damien Scieur, Francis Bach, Alexandre d'Aspremont
Balancing information exposure in social networks
Kiran Garimella, Aristides Gionis, Nikos Parotsidis et al.
Active Exploration for Learning Symbolic Representations
Garrett Andersen, George Konidaris
Natural Value Approximators: Learning when to Trust Past Estimates
Zhongwen Xu, Joseph Modayil, Hado P van Hasselt et al.
EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms
Yogatheesan Varatharajah, Min Jin Chong, Krishnakant Saboo et al.
Asynchronous Coordinate Descent under More Realistic Assumptions
Tao Sun, Robert Hannah, Wotao Yin
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum, Mohammad Norouzi, Kelvin Xu et al.
Cold-Start Reinforcement Learning with Softmax Policy Gradient
Nan Ding, Radu Soricut
Filtering Variational Objectives
Chris J Maddison, John Lawson, George Tucker et al.
Parametric Simplex Method for Sparse Learning
Haotian Pang, Han Liu, Robert J Vanderbei et al.
Language Modeling with Recurrent Highway Hypernetworks
Joseph Suarez
The Reversible Residual Network: Backpropagation Without Storing Activations
Aidan N Gomez, Mengye Ren, Raquel Urtasun et al.
Variational Inference for Gaussian Process Models with Linear Complexity
Ching-An Cheng, Byron Boots
Gradient Episodic Memory for Continual Learning
David Lopez-Paz, Marc'Aurelio Ranzato
Universal consistency and minimax rates for online Mondrian Forests
Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit
Laurence Aitchison, Lloyd Russell, Adam M Packer et al.
Dual Path Networks
Yunpeng Chen, Jianan Li, Huaxin Xiao et al.
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon S Du, Chi Jin, Jason Lee et al.
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian, Ce Zhang, Huan Zhang et al.
Overcoming Catastrophic Forgetting by Incremental Moment Matching
Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun et al.