Training Neural Networks at Any Scale Volkan Cevher, Associate Professor, School of Engineering, Swiss Federal Institute of Technology (EPFL), Switzerland Nov 24, 12:00 - 13:00 B9 L2 R2325 machine learning Numerical simulation and analysis Reinforcement Learning deep learning optimization
First Provably Optimal Asynchronous SGD for Homogeneous and Heterogeneous Data Arto Maranjyan, Ph.D. Student, Computer Science Nov 13, 12:00 - 13:00 B9 L2 R2325 machine learning optimization asynchronous algorithms Training
BiCoLoR: Communication-Efficient Optimization with Bidirectional Compression and Local Training Laurent Condat, Senior Research Scientist, Computer Science Oct 27, 12:00 - 13:00 B9 L2 R2325 optimization Distributed algorithms Signal and Image Processing
From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs Peter Richtarik, Professor, Computer Science Sep 15, 12:00 - 13:00 B9 L2 R2325 AI machine learning optimization algorithms LLM
From the Ball-Proximal (Broximal) Point Method to Efficient Training of LLMs Peter Richtarik, Professor, Computer Science Sep 4, 12:00 - 13:00 B9 L2 R2325 AI machine learning optimization algorithms LLM
Error Feedback for Communication-Efficient First and Second-Order Distributed Optimization: Theory and Practical Implementation Konstantin Burlachenko, Ph.D. Student, Computer Science May 12, 12:00 - 13:00 B9 L2 R2325 Federated learning software development
Proximal Splitting Methods for Convex Optimization: An Introduction Laurent Condat, Senior Research Scientist, Computer Science Dec 2, 12:00 - 13:00 B9 L2 H1 R2322
Langevin Monte Carlo as an optimization algorithm Adil Salim, Postdoctoral Research Fellow, Computer Science Nov 11, 12:00 - 13:00 B9 L2 H1 R2322 machine learning Langevin Monte Carlo optimization
