Local Rademacher Complexity Machine
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.10.087
Abstract: Abstract Support Vector Machines (SVMs) are a state-of-the-art and powerful learning algorithm that can effectively solve many real world problems. SVMs are the transposition of the Vapnik–Chervonenkis (VC) theory into a learning algorithm. In this… read more here.
Keywords: rademacher complexity; complexity machine; learning algorithm; local rademacher ... See more keywords
Non-IID Federated Learning With Sharper Risk Bound.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3213187
Abstract: In federated learning (FL), the not independently or identically distributed (non-IID) data partitioning impairs the performance of the global model, which is a severe problem to be solved. Despite the extensive literature related to the… read more here.
Keywords: local rademacher; non iid; federated learning; risk ... See more keywords