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Kun Yang

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.DC1
same name
  • Kun Yang — 64 papers, h 33
  • Kun Yang — 21 papers
  • Kun Yang — 19 papers, h 52
  • Kun Yang — 8 papers
  • Kun Yang — 7 papers
  • Kun Yang — 4 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedSecure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Adaptive Requesting in Decentralized Edge Networks via Non-Stationary Bandits

Yi Zhuang, Kun Yang, Xingran Chen

We study a decentralized collaborative requesting problem that aims to optimize the information freshness of time-sensitive clients in edge networks consisting of multiple clients,…

cs.LG2025★ 1 cited

Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation

Kun Yang, Neena Imam

Federated Learning (FL) enables collaborative machine learning across decentralized data sources without sharing raw data. It offers a promising approach to privacy-preserving AI.…

cs.LG2025

Financial Data Analysis with Robust Federated Logistic Regression

Kun Yang, Nikhil Krishnan, Sanjeev R. Kulkarni

In this study, we focus on the analysis of financial data in a federated setting, wherein data is distributed across multiple clients or locations, and the raw data never leaves th…

cs.DC2024

A Seesaw Model Attack Algorithm for Distributed Learning

Kun Yang, Tianyi Luo, Yanjie Dong +1

We investigate the Byzantine attack problem within the context of model training in distributed learning systems. While ensuring the convergence of current model training processes…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.