<strike id="fnjzd"></strike>
<strike id="fnjzd"><dl id="fnjzd"></dl></strike>
<strike id="fnjzd"></strike>
<strike id="fnjzd"><dl id="fnjzd"><del id="fnjzd"></del></dl></strike>
<th id="fnjzd"></th>
<strike id="fnjzd"><dl id="fnjzd"><ruby id="fnjzd"></ruby></dl></strike>
<strike id="fnjzd"><dl id="fnjzd"></dl></strike>
<th id="fnjzd"><dl id="fnjzd"><strike id="fnjzd"></strike></dl></th><span id="fnjzd"></span>
<span id="fnjzd"></span>
<strike id="fnjzd"></strike><th id="fnjzd"><video id="fnjzd"><strike id="fnjzd"></strike></video></th>
新闻公告
您当前位置: 学院首页 > 通知公告 > 正文

“第二届经纬青年学者论坛”学术报告

2019年09月05日 17:10  点击:[]

第二届经纬青年学者论坛学术报告


报告时间:2019年9月6日(星期五)上午9:10

报告地点:临潼校区计算机科学学院618报告厅

报告:Ranking Preserving Nonnegative Matrix Factorization

报告人:王晶(日本东京大学博士后)

报告内容:Nonnegative matrix factorization (NMF), a well-known technique to find parts-based representations of nonnegative data, has been widely studied. In reality, ordinal relations often exist among data,such as dataiis more related tojthan toq. Such relative order is naturally available, and more importantly, it truly reflects the latent data structure. Preserving the ordinal relations enables us to find structured representations of data that are faithful to the relative order, so that the learned representations become more discriminative. However, this cannot be achieved by current NMFs. In thispresentation,Dr. Wangmake the attempt towards incorporating the ordinal relations and propose a novel ranking preserving nonnegative matrix factorization (RPNMF) approach, which enforces the learned representations to be ranked according to the relations.Shederive iterative updating rules to solve RPNMF’s objective function with convergence guaranteed. Experimental results with several datasets for clustering and classification have demonstrated that RPNMF achieves greater performance against the state-of-the-arts, not only in terms of accuracy, but also interpretation of orderly data structure.

报告:Brief talk about VRandAR

报告人:马弘霖(麻省理工大学博士,现任苹果公司高级工程师)

报告内容:In recent years京城彩票平台注册,VR technology develop rapidly.The virtual realityis widely used in our daily life.Dr. Mawillintroduce how VR technology can change people's daily lives, especially in education, medical care, tourism, and others insights that have changed which could influenced us. And how we develop our own VR hardware software products. Similarly, we use VR an technologies together to develop new technology products that change traditional industries.

报告:Hyperbolic Space for Hierarchical Data Embedding

报告人:Atsushi Suzuki(日本东京大学博士生)

报告内容:Embedding refers to a map from a object set to a space, with additional information preserved. Here, additional information includes an edge set in graph embedding setting and a distance matrix in metric multi-dimensional scaling. Although existing approaches have preserved such additional information in Euclidean space, whether Euclidean space is compatible with true data structure is largely ignored. which is essential to effective embedding. Since real data often exhibit hierarchical structure, it is hard for Euclidean space approaches to achieve effective embeddings in low dimensionality, which incurs high computational complexity or overfitting. Recent work has solved this problem by using hyperbolic space. In presentation,Mr. Suzukibriefly explain some basic properties of hyperbolic space, and how hyperbolic space works on embedding of hierarchical data.

欢迎教师及学生积极参加京城彩票平台注册!

计算机科学学院

2019年9月4日

报告人简介:王晶,现任日本东京大学博士后京城彩票平台注册,研究领域包括机器学习京城彩票平台注册,数据挖掘,专攻降维京城彩票平台注册,聚类,多视角学习等。2018年1月于英国伯恩茅斯取得博士学位。在此之前,于香港城市大学取得多媒体资讯科技硕士学位京城彩票平台注册。博期间以访问学生身份访问法国蒙彼利埃第二大学,美国纽约大学 和 以EU Marie Curie访问学者身份访问了澳大利亚查尔斯特大学。 博士期间凭借其研究成果获得全英“2017 ABTA Doctoral research award”工程自然科学类第二名。 目前共发表论文近20篇,其中包括CCF-A类会议AAAI 2019, IJCAI 2019京城彩票平台注册,2018,2017,KDD 2019以及JCR-1区期刊IEEE transactions on Cybernetics, IEEE transactions on Image Processing等京城彩票平台注册。并担任国际期刊及会议审稿人,包括AAAI 2020, 2019, TKDE, TIP, IEEE access等。

马弘霖,博士。2010年获得麻省理工大学博士学位,现任苹果公司高级工程师职位京城彩票平台注册;主要从事人工智能VR,AR可穿戴设备方面的研究工作京城彩票平台注册, 在可穿戴设备方面取得了一系列丰富的科研成果。其中京城彩票平台注册,以第一作者身份发表论文6篇;申请专利5项,其中发明专利2项,授权实用新型专利3项京城彩票平台注册;参与美国宇航员培训系统等项目的研究工作京城彩票平台注册。

Atsushi Suzuki (铃木 惇), who is a third-year JSPS funded phd student in the graduate school of information science and technology of the University of Tokyo. Previous to that, he obtained both master and bachelor degrees from the same university. His research mainly focuses on deep learning, tensor factorization, information theory, statistics and so on.He has published several papers in top conferences, including ICDM, ISIT, AAAI, IJCAI, etc.

下一条:计算机科学学院2019届优秀毕业生、优秀毕业生干部评定结果公示

关闭

Copyright(c)2016 西安工程大学计算机科学学院 地址:中国·西安·临潼区·陕鼓大道58号[710600]
联系我们:webmaster@xpu.edu.cn 陕ICP备022000
京城彩票平台注册