no code implementations • 25 Apr 2024 • MD Kamran Chowdhury Shisher, Yin Sun, I-Hong Hou
In addition, we design low-complexity scheduling policies to improve inference performance.
no code implementations • 6 Apr 2024 • I-Hong Hou
In addition to the exploration-exploitation dilemma in the traditional multi-armed bandit problem, we show that the consideration of multiple stages introduces a third component, education, where an agent needs to choose its actions to facilitate the learning of agents in the next stage.
no code implementations • 22 Mar 2024 • Xin Chen, I-Hong Hou
This paper introduces a novel multi-armed bandits framework, termed Contextual Restless Bandits (CRB), for complex online decision-making.
1 code implementation • 18 Sep 2022 • Khaled Nakhleh, I-Hong Hou
We consider the problem of learning the optimal threshold policy for control problems.
1 code implementation • NeurIPS 2021 • Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai
This paper proposes NeurWIN, a neural Whittle index network that seeks to learn the Whittle indices for any restless bandits by leveraging mathematical properties of the Whittle indices.