{"id":"url:paperswithcode.com/paper/optimizing-millions-of-hyperparameters-by","title":"Optimizing Millions of Hyperparameters by Implicit Differentiation","date":"2019-11-06","section":"Data, training, optimization","quality":null,"url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/c5ceae5fd961be6d0bb1cd78bdf473d8b86954dc0615b3fb35ad9124be5e2643/","source_url":"https://paperswithcode.com/paper/optimizing-millions-of-hyperparameters-by","text_available":false,"authors":["Jonathan Lorraine","Paul Vicol","David Duvenaud"],"outgoing":[],"incoming":[{"source":"arxiv:2402.02342","target":"url:paperswithcode.com/paper/optimizing-millions-of-hyperparameters-by","evidence":"title","id":"arxiv:2402.02342","title":"MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters","url":"https://vinnik-dmitry07.github.io/favorite-papers/agents/papers/6801d4fe20b85924aed2dec1855a35232b2ec1d98e15ec3bc27a0fbe5dfd1af7/"}],"text_parts":[],"contents":[],"text_code_points":0,"source_markdown":null}