Federated Learning in Temporal Heterogeneity

no code implementations • 17 Sep 2023 • Junghwan Lee

In this work, we explored federated learning in temporal heterogeneity across clients.

Federated Learning

Deep Attention Q-Network for Personalized Treatment Recommendation

1 code implementation • 4 Jul 2023 • Simin Ma, Junghwan Lee, Nicoleta Serban, Shihao Yang

Tailoring treatment for individual patients is crucial yet challenging in order to achieve optimal healthcare outcomes.

Deep Attention reinforcement-learning

Neural network-based CUSUM for online change-point detection

no code implementations • 31 Oct 2022 • Tingnan Gong, Junghwan Lee, Xiuyuan Cheng, Yao Xie

Change-point detection, detecting an abrupt change in the data distribution from sequential data, is a fundamental problem in statistics and machine learning.

Change Point Detection Computational Efficiency

Epistasis-based Basis Estimation Method for Simplifying the Problem Space of an Evolutionary Search in Binary Representation

no code implementations • 19 Apr 2019 • Junghwan Lee, Yong-Hyuk Kim

An evolutionary search space can be smoothly transformed via a suitable change of basis; however, it can be difficult to determine an appropriate basis.