changepoint detection 1conformal inference 1meta-learning 1robust statistics 1root cause analysis 1uncertainty weighting 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Conformal Changepoint Localization and Root Cause Analysis with Corrupted Observations
Seunghun Yu, Meiyi Zhu, Petar Popovski +2
The paper proposes weighted conformal methods for changepoint localization and root‑cause analysis that downweight potentially corrupted observations using uncertainty estimates, a…
cs.LG2026
FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels
Seunghun Yu, Jin-Hyun Ahn, Joonhyuk Kang
Federated Learning (FL) is a powerful framework for privacy-preserving distributed learning. It enables multiple clients to collaboratively train a global model without sharing raw…
cs.LG2025
CG-FKAN: Compressed-Grid Federated Kolmogorov-Arnold Networks for Communication Constrained Environment
Seunghun Yu, Youngjoon Lee, Jinu Gong +1
Federated learning (FL), widely used in privacy-critical applications, suffers from limited interpretability, whereas Kolmogorov-Arnold Networks (KAN) address this limitation via l…