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Reinforcement Learning

2932 directly classified papers

Papers per year

Papers

A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation ICML 2021
Detecting Rewards Deterioration in Episodic Reinforcement Learning ICML 2021
Bootstrapping Fitted Q-Evaluation for Off-Policy Inference ICML 2021
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation ICML 2021
Generalizable Episodic Memory for Deep Reinforcement Learning ICML 2021
Objective Bound Conditional Gaussian Process for Bayesian Optimization ICML 2021
Prioritized Level Replay ICML 2021
Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management AAAI 2021
DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding AAAI 2021
Hierarchically and Cooperatively Learning Traffic Signal Control AAAI 2021
Online 3D Bin Packing with Constrained Deep Reinforcement Learning AAAI 2021
DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems AAAI 2021
A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models AAAI 2021
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation AAAI 2021
Learning to Recommend from Sparse Data via Generative User Feedback AAAI 2021
A General Offline Reinforcement Learning Framework for Interactive Recommendation AAAI 2021
Encoding Human Domain Knowledge to Warm Start Reinforcement Learning AAAI 2021
AI-Assisted Scientific Data Collection with Iterative Human Feedback AAAI 2021
Learning Rewards From Linguistic Feedback AAAI 2021
A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving AAAI 2021
An Enhanced Advising Model in Teacher-Student Framework using State Categorization AAAI 2021
Deep Radial-Basis Value Functions for Continuous Control AAAI 2021
Reinforcement Learning with Trajectory Feedback AAAI 2021
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning AAAI 2021
Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances AAAI 2021