Original title: Probabilistic Inference in Reinforcement Learning Done Right Authors: Jean Tarbouriech, Tor Lattimore, Brendan O’Donoghue In their article, researchers explore Reinforcement Learning (RL) through a probabilistic lens, focusing on Markov decision processes (MDP) and…
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Original title: Combinatorial Optimization with Policy Adaptation using Latent Space Search Authors: Felix Chalumeau, Shikha Surana, Clement Bonnet, Nathan Grinsztajn, Arnu Pretorius, Alexandre Laterre, Thomas D. Barrett The challenge of solving complex problems like Combinatorial…
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Original title: Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model Authors: Kai Yang, Jian Tao, Jiafei Lyu, Chunjiang Ge, Jiaxin Chen, Qimai Li, Weihan Shen, Xiaolong Zhu, Xiu Li In the world…
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Original title: Probabilistic Inference in Reinforcement Learning Done Right Authors: Jean Tarbouriech, Tor Lattimore, Brendan O’Donoghue In this article, the world of Reinforcement Learning (RL) unfolds like an intricate puzzle. Imagine diving into a realm…
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Original title: Risk-sensitive Markov Decision Process and Learning under General Utility Functions Authors: Zhengqi Wu, Renyuan Xu In this article, the focus is on Reinforcement Learning (RL) and its application in diverse fields. RL theory…
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Original title: ChatGPT and post-test probability Authors: Samuel J. Weisenthal The article explores how ChatGPT, a reinforcement learning-based language model, tackles probabilistic medical diagnostic reasoning, a crucial task in healthcare. It investigates ChatGPT’s capability in…
