80 citations · 118 across the 5 of their papers we have counts for
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cs.LG2020
LINDT: Tackling Negative Federated Learning with Local Adaptation
Hong Lin, Lidan Shou, Ke Chen +2
Federated Learning (FL) is a promising distributed learning paradigm, which allows a number of data owners (also called clients) to collaboratively learn a shared model without dis…
cs.LG2020★ 80 cited
Feature Importance Ranking for Deep Learning
Maksymilian Wojtas, Ke Chen
Feature importance ranking has become a powerful tool for explainable AI. However, its nature of combinatorial optimization poses a great challenge for deep learning. In this paper…
cs.LG2020★ 3 cited
A Framework for End-to-End Learning on Semantic Tree-Structured Data
William Woof, Ke Chen
While learning models are typically studied for inputs in the form of a fixed dimensional feature vector, real world data is rarely found in this form. In order to meet the basic r…