Eric Moulines: On stochastic proximal gradient algorithms
Presented January 16th, 2014 at the University of Florida by the Laboratory for Cognition and Control in Complex Systems.
More info: http://ccc.centers.ufl.edu/?q=ccc_workshop_2014
Visit us! http://ccc.centers.ufl.edu
Видео Eric Moulines: On stochastic proximal gradient algorithms канала cccUF
More info: http://ccc.centers.ufl.edu/?q=ccc_workshop_2014
Visit us! http://ccc.centers.ufl.edu
Видео Eric Moulines: On stochastic proximal gradient algorithms канала cccUF
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Peter Caines: Recent Developments in Mean Field Control
Gregory Puleo - Community Detection via Correlation Clustering Algorithm Improvements
Karl McDermott: Regulatory Lag and How to Recover the Costs of New Infrastructure
Zap Q-learning with Nonlinear Function Approximation
Adithya M Devraj - Differential TD Learning to Approximate the Solution to Poisson's Equation
Yves Atchadé - Iterated Filtering Algorithms
Karl McDermott: The Home as a Power Plant
Johanna Mathieu: Harnessing Residential Loads for Demand Response
Maxim Raginsky: Concentration of Measure Inequalities in Information Theory, Communications + Coding
Muriel Medard - Going on Twenty - Network Coding
Prof. Joe Chow's lecture
Michelle Effros: On Communication, Control, and the Cost of Seperation
Sean Meyn - Modeling Nature in Linearly Scalable MDPs
Maryam Shanechi USC Next-Generation Brain-Machine Interface Systems
Jean-Yves Le Boudec: Real Time Control of Distribution Networks
Maxim Raginsky: The limits of control: An information-theoretic viewpoint
Shaofeng Zou University of Buffalo Robust Reinforcement Learning Under Model Uncertainty
Vivek Borkar: Relative Value for Ergodic Control of Diffusions
Anand Radhakrishnan - Variance reduction in MCMC using control variates
Murial Medard: Joint source, channel and network coding- a simple ad-hoc approach