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Research Group

Stich

Optimization is at the heart of many machine learning algorithms. The focus of our research group is on fundamental research on optimization techniques for training machine learning models. The research topics include decentralized methods (collaborative learning, federated learning), but also adaptive stochastic methods, generalization performance, deep theory of deep learning, and privacy and security in machine learning.

Head of Group

Sebastian Stich

Email

Address

Im Oberen Werk 1
66386 St. Ingbert (Germany)

Most Recent Publications

Year 2026

Conference / Medium

International Conference on Artificial Intelligence and Statistics (AISTATS)
Accelerated Distributed Optimization with Compression and Error Feedback

Conference / Medium

International Conference on Learning Representations (ICLR)
Composite Optimization with Error Feedback: the Dual Averaging Approach

Conference / Medium

International Conference on Learning Representations (ICLR)
Non-Convex Federated Optimization under Cost-Aware Client Selection

Conference / Medium

International Conference on Learning Representations (ICLR)
FedMuon: Federated Learning with Bias-corrected LMO-based Optimization