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07/06/2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation
Risk-sensitive reinforcement learning (RL) aims to optimize policies tha...
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08/30/2022
Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning
Multi-user delay constrained scheduling is important in many real-world ...
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06/23/2022
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
We study reinforcement learning with linear function approximation where...
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05/30/2022
RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
Training deep reinforcement learning (DRL) models usually requires high ...
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02/21/2018
Optimal Multi-User Scheduling of Buffer-Aided Relay Systems
Multi-User scheduling is a challenging problem under the relaying scenar...
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02/16/2018
Optimal Hybrid Full-Duplex/Half-Duplex Scheme for Buffer Aided Relay Systems
Full-duplex (FD) communication has received great interest in recent yea...
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02/16/2018