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cs.LG2025
Why Federated Optimization Fails to Achieve Perfect Fitting? A Theoretical Perspective on Client-Side Optima
Zhongxiang Lei, Qi Yang, Ping Qiu +3
Federated optimization is a constrained form of distributed optimization that enables training a global model without directly sharing client data. Although existing algorithms can…
cs.LG2025
SEMPO: Lightweight Foundation Models for Time Series Forecasting
Hui He, Kun Yi, Yuanchi Ma +3
The recent boom of large pre-trained models witnesses remarkable success in developing foundation models (FMs) for time series forecasting. Despite impressive performance across di…
cs.LG2024
Masked AutoEncoder for Graph Clustering without Pre-defined Cluster Number k
Yuanchi Ma, Hui He, Zhongxiang Lei +1
Graph clustering algorithms with autoencoder structures have recently gained popularity due to their efficient performance and low training cost. However, for existing graph autoen…