{"title":"深度学习只能是神经网络吗?","authors":"Zhi-Hua Zhou","doi":"10.1145/3336191.3372190","DOIUrl":null,"url":null,"abstract":"The word \"deep learning\" is generally regarded as a synonym of \"deep neural networks (DNNs)\". In this talk, we will discuss on essentials in deep learning and claim that deep learning is not necessarily to be realized by neural networks and differentiable modules. We will then present an exploration to non-NN style deep learning, where the building blocks are non-differentiable modules and the training process does not rely on backpropagation or gradient-based adjustment. We will also talk about some recent advances and challenges in this direction of research.","PeriodicalId":319008,"journal":{"name":"Proceedings of the 13th International Conference on Web Search and Data Mining","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can Deep Learning Only Be Neural Networks?\",\"authors\":\"Zhi-Hua Zhou\",\"doi\":\"10.1145/3336191.3372190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The word \\\"deep learning\\\" is generally regarded as a synonym of \\\"deep neural networks (DNNs)\\\". In this talk, we will discuss on essentials in deep learning and claim that deep learning is not necessarily to be realized by neural networks and differentiable modules. We will then present an exploration to non-NN style deep learning, where the building blocks are non-differentiable modules and the training process does not rely on backpropagation or gradient-based adjustment. We will also talk about some recent advances and challenges in this direction of research.\",\"PeriodicalId\":319008,\"journal\":{\"name\":\"Proceedings of the 13th International Conference on Web Search and Data Mining\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 13th International Conference on Web Search and Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3336191.3372190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th International Conference on Web Search and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3336191.3372190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The word "deep learning" is generally regarded as a synonym of "deep neural networks (DNNs)". In this talk, we will discuss on essentials in deep learning and claim that deep learning is not necessarily to be realized by neural networks and differentiable modules. We will then present an exploration to non-NN style deep learning, where the building blocks are non-differentiable modules and the training process does not rely on backpropagation or gradient-based adjustment. We will also talk about some recent advances and challenges in this direction of research.