Deep and Convolutional Networks: Generalization and Optimization
Graph Chatbot
Chat with Graph Search
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.
Explores the intersection between neuroscience and machine learning, discussing deep learning, reinforcement learning, memory systems, and the future of bridging machine and human-level intelligence.
Explores the impact of gradient noise on optimization algorithms, focusing on smooth and nonsmooth risk functions and the derivation of gradient noise moments.
Explores advanced optimization techniques for machine learning models, focusing on adaptive gradient methods and their applications in non-convex optimization problems.
Explores challenges and solutions for scalable and trustworthy learning in heterogeneous networks, emphasizing data heterogeneity, privacy, fairness, and robustness.
