Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Covers the BackProp algorithm, including initialization, signal propagation, error computation, weight updating, and complexity comparison with numerical differentiation.
Discusses the mean input shift and bias problem in weight updates for neural networks, highlighting the importance of correct initialization to prevent gradient issues.
Explores the impact of gradient noise on optimization algorithms, focusing on smooth and nonsmooth risk functions and the derivation of gradient noise moments.
