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Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
Mahmoud ("Mido") Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat
Neural Information Processing Systems http://nips.cc/
BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos
Eleanor Batty, Matthew Whiteway, Shreya Saxena, Dan Biderman, Taiga Abe, Simon Musall, Winthrop Gillis, Jeffrey Markowitz, Anne Churchland, John P. Cunningham, Sandeep R. Datta, Scott Linderman, Liam Paninski
Neural Information Processing Systems http://nips.cc/
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function
Aviv Rosenberg, Yishay Mansour
We consider online learning in episodic loop-free Markov decision processes (MDPs), where the loss function can change arbitrarily between episodes.
We propose a post hoc saliency-based explanation framework for counterfactual reasoning in probabilistic multivariate time-series forecasting (regression) settings
Building upon Miller's framework of explanations derived from research in multiple
Boosting Black Box Variational Inference
Francesco Locatello, Gideon Dresdner, Rajiv Khanna, Isabel Valera, Gunnar Raetsch
Convex Optimizationwithout Projection Steps.arXivmath.OC, August 2011.
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability
Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, Yan Liu
Please note that an "interaction" in this paper is a statistical interaction that describes a non-additive