[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-error-feedback":3},{"tag":4,"articles":10},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":9},"c21e156e-4e6d-4b52-80bc-10b242c78177","error feedback","error-feedback",0,null,[11],{"id":12,"slug":13,"title":14,"summary":15,"category":16,"image_url":17,"cover_image":17,"language":18,"created_at":19},"2259a53b-8fe2-484e-a831-7dc862e98168","tight-theory-error-feedback-distributed-optimization-zh","壓縮式分散最佳化理論再收緊","這篇論文把壓縮式分散最佳化中 EF 與 EF21 的收斂理論收得更緊，並給出更精準的步長與 Lyapunov 分析。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780295585699-e1jz.png","zh","2026-06-01T06:32:36.7027+00:00"]