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  • 杭州電子科技大學·計算機學院

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    【學術報告會】日本理化學研究院(RIKEN)趙啟斌研究員學術報告會通知

    閱讀量:223 發布時間:2019-12-30 13:43:11

    報告人:日本理化學研究院(RIKEN)先進智能研究中心趙啟斌研究員

    報告題目:Tensor Network Representations in Machine Learning

    報告時間:20191231日(周二)下午 1400-1500

    報告地點:學院三樓會議室

    歡迎廣大師生參會學習交流! 


    報告人簡介:

    趙啟斌教授2009年獲得上海交通大學博士學位,2009年赴日本理化學研究院(RIKEN)腦科學所從事腦信號處理方面的研究,2016年加入剛成立的日本理化學研究院(RIKEN)先進智能研究中心任研究室主任,從事人工智能理論及應用研究。趙博士主要從事領域包括機器學習、張量分析、神經計算、腦-機接口及計算機視覺等,已發表學術論文30余篇,在頂級期刊TPAMI發表論文兩篇。

    報告摘要:

    Tensor networks are factorizations of very large tensors into networks of smaller tensors, it is shown to be a general extension of typical tensor decomposition to high dimensional case.  Recently, tensor networks are also increasingly finding applications in machine learning such as model compression or acceleration of computations. In this talk, I will firstly present the general concept of tensor network related research in machine learning, and then introduce our studies on fundamental tensor network model, algorithm, and applications. In particular, the tensor ring decomposition model is introduced and shown to be powerful and efficient representations. In addition, we will present recent progresses on how tensor networks can be employed to solve challenging problems in tensor completion, multi-task learning and multi-modal learning.


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