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Deep RL

3861 directly classified papers

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Papers

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing NIPS 2018
Context-dependent upper-confidence bounds for directed exploration NIPS 2018
Fast deep reinforcement learning using online adjustments from the past NIPS 2018
Scalable Bilinear Pi Learning Using State and Action Features ICML 2018
Mix & Match Agent Curricula for Reinforcement Learning ICML 2018
Learning Globally Optimized Object Detector via Policy Gradient CVPR 2018
Dynamic Zoom-In Network for Fast Object Detection in Large Images CVPR 2018
Deep Reinforcement Learning of Region Proposal Networks for Object Detection CVPR 2018
Generative Temporal Models with Spatial Memory for Partially Observed Environments ICML 2018
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning ICML 2018
Dual Policy Iteration NIPS 2018
Scalable Coordinated Exploration in Concurrent Reinforcement Learning NIPS 2018
Meta-Gradient Reinforcement Learning NIPS 2018
Recurrent World Models Facilitate Policy Evolution NIPS 2018
Q-learning with Nearest Neighbors NIPS 2018
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes NIPS 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models NIPS 2018
An Off-policy Policy Gradient Theorem Using Emphatic Weightings NIPS 2018
Randomized Prior Functions for Deep Reinforcement Learning NIPS 2018
On Oracle-Efficient PAC RL with Rich Observations NIPS 2018
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning NIPS 2018
Policy Optimization via Importance Sampling NIPS 2018
Transfer of Deep Reactive Policies for MDP Planning NIPS 2018
Unsupervised Learning based Jump-Diffusion Process for Object Tracking in Video Surveillance IJCAI 2018
Goal-HSVI: Heuristic Search Value Iteration for Goal POMDPs IJCAI 2018