About Grigory Malinovsky Grigory Malinovsky Ph.D. Student, Applied Mathematics and Computational Science machine learning optimization applied statistics stochastic optimization distributed optimization Federated learning Events Presented Events Jun 14 - Jun 20, 2026 Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization Grigory Malinovsky, Ph.D. Student, Applied Mathematics and Computational Science Jun 18, 15:45 - 19:00 B5 R5209 machine learning Federated learning distributed optimization applied statistics This thesis investigates seven critical challenges at the intersection of theory and practice, specifically focusing on the fundamental bottlenecks of Federated Learning and distributed optimization and develops novel algorithmic frameworks that provide sharp theoretical guarantees to bridge the gap between heuristic success and mathematical rigor.
Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization Grigory Malinovsky, Ph.D. Student, Applied Mathematics and Computational Science Jun 18, 15:45 - 19:00 B5 R5209 machine learning Federated learning distributed optimization applied statistics This thesis investigates seven critical challenges at the intersection of theory and practice, specifically focusing on the fundamental bottlenecks of Federated Learning and distributed optimization and develops novel algorithmic frameworks that provide sharp theoretical guarantees to bridge the gap between heuristic success and mathematical rigor.
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