Workshop on Distributed Computing, Optimization & Learning (WDCL)

Distributed computing plays an ever-increasing role in accelerating non-linear and computationally hard tasks. As the complexity of these tasks increases, research seeks novel parallel processing techniques to efficiently offload computations to groups of distributed servers, under various frameworks such as MapReduce and Spark. Distributed computing naturally entails several challenges that involve accuracy, scalability, privacy and security, as well as latency and straggler mitigation.

The Workshop on Distributed Computing, Optimization & Learning (WDCL) is an international scientific workshop dedicated to distributed computing, distributed learning, and communication-computation trade-offs. WDCL brings expert researchers from academia and industry with various backgrounds and various active topics in research, including

• Distributed optimization, control, and coordination

• Efficient distributed and federated learning

• Privacy, security, and trustworthy distributed computation

• Information-theoretic foundations of learning and generalization

• Communication-efficient learning over wireless and edge networks

• Robust, dependable, and resilient distributed systems

• Coding, coded computing, and computation–communication tradeoffs

• Fairness, game theory, and incentives in networked learning systems

Latest Edition

• WDCL 2026, University of Cyprus (UCY), Nicosia, Cyprus, Oct. 14-16, 2026.

Previous Editions

• WDCL 2025, TUM, Munich, Germany, Sep. 3-5, 2025.

• WDCL 2024, ISEP auditorium, in Issy-les-Moulineaux, France, 22-23 May, 2024.