Dataset condensation for recommendation
Training recommendation models on large datasets often requires significant time and
computational resources. Consequently, an emergent imperative has arisen to construct …
computational resources. Consequently, an emergent imperative has arisen to construct …
Learnable behavior control: Breaking atari human world records via sample-efficient behavior selection
The exploration problem is one of the main challenges in deep reinforcement learning (RL).
Recent promising works tried to handle the problem with population-based methods, which …
Recent promising works tried to handle the problem with population-based methods, which …
Generalized data distribution iteration
To obtain higher sample efficiency and superior final performance simultaneously has been
one of the major challenges for deep reinforcement learning (DRL). Previous work could …
one of the major challenges for deep reinforcement learning (DRL). Previous work could …
A review for deep reinforcement learning in atari: Benchmarks, challenges, and solutions
J Fan - arXiv preprint arXiv:2112.04145, 2021 - arxiv.org
The Arcade Learning Environment (ALE) is proposed as an evaluation platform for
empirically assessing the generality of agents across dozens of Atari 2600 games. ALE …
empirically assessing the generality of agents across dozens of Atari 2600 games. ALE …