[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-optimal-transport":3},{"tag":4,"articles":10},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":9},"630d85e9-6972-4682-aa35-fc80ff37c71e","optimal transport","optimal-transport",2,null,[11],{"id":12,"slug":13,"title":14,"summary":15,"category":16,"image_url":17,"cover_image":17,"language":18,"created_at":19},"84f424fe-d45e-485f-994c-62f2e9f407b9","hycnns-convex-learning-optimal-transport-zh","HyCNNs：更省參數的凸函數學習","HyCNNs 把 Maxout 和 ICNN 結合，主打更有效率地學凸函數，並在凸迴歸、插值與高維最適傳輸上展現優勢。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1777530051534-pe7e.png","zh","2026-04-30T06:20:35.849921+00:00"]