Opportunistic Episodic Reinforcement Learning

no code implementations • 24 Oct 2022 • Xiaoxiao Wang, Nader Bouacida, Xueying Guo, Xin Liu

In this paper, we propose and study opportunistic reinforcement learning - a new variant of reinforcement learning problems where the regret of selecting a suboptimal action varies under an external environmental condition known as the variation factor.

reinforcement-learning Reinforcement Learning (RL)

Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning

no code implementations • 8 Nov 2020 • Nader Bouacida, Jiahui Hou, Hui Zang, Xin Liu

With more regulations tackling users' privacy-sensitive data protection in recent years, access to such data has become increasingly restricted and controversial.

BIG-bench Machine Learning Federated Learning

An Opportunistic Bandit Approach for User Interface Experimentation

no code implementations • 21 Jun 2020 • Nader Bouacida, Amit Pande, Xin Liu

In fact, we model user interface experimentation as an opportunistic bandit problem, in which the cost of exploration varies under a factor extracted from customer features.