深度学习短期班

Selected topics in deep learning

Dr. G. Montufar

Max-Planck Institute for Mathematics in the Sciences

Abstract

This is a short course concerning some selected topics in deep learning. The course has three blocks. Each block will take about 2 hours. The following are the topics that will be covered in this course.

lRepresentational power of feedforward neural networks and probabilistic models;

lReinforcement learning (Structure of the optimization landscape, how to choose an approximation neural network);

lUnsupervised training;

lDimension of related algebraic varieties.

地点: 理科楼M842报告厅
时间: 7月12日—7月13日, 14:00-16:00,  
         7月14日, 9:00-11:00
授课人简介:
Dr. G. Montufar received his Ph.D in Mathematics from Leipzig Univerisity in 2012. He is currently a post-doc researcher at Max-Planck Institute for Mathematics in the Sciences, and will become an Assistant Professor at UCLA soon. His research interests are very broad, including deep learning, design of learning systems, data compression, graphical models, information geometry and so on.