題 目:Approximate Graph and Hypergraph Partitions via Semidefinite Programming and Tensor Methods
内容簡介:With recent advance in graph and hypergraph, the partitioning and clustering based on hypergraphs are relevant for various applications in machine learning, computer vision, bioinformatics, and very large scale integration (VLSI) design. In general, most partitioning problems are NP-hard and even hard to approximate. With the advent of ever instances in various applications, approximating graph and hypergraph partition problems become more and more important and challenging. In the talk, we will introduce our recent results on approximating graph and hypergraph partitioning problems via semidefinite programming and tensor spectral techniques.
報告人:張曉岩
報告人簡介:先後獲南開大學應用數學博士學位和荷蘭特文特大學理論計算機科學博士學位,南京師範大學數學科學學院及數學研究所教授、博士生導師、統計學博士後合作導師,中科院深圳先進技術研究院數字所高性能計算中心客座研究員,國家重大人才領軍計劃入選者,江蘇省六大人才高峰高層次人才入選者,江蘇省智庫青年人才計劃入選者,中國運籌學圖論與組合分會常務理事,中國運籌學數學規劃分會理事,中國運籌學算法軟件與應用分會理事,中國運籌學數學與智能分會理事,中國計算機學會理論計算機科學專業委員會執行委員,研究成果發表在《SIAM J. Computing》、《SIAM J. Scientific Computing》、《SIAM J. Discrete Math》、《IEEE Transactions on information Theory》等國際著名期刊,著有英文學術論著兩部及譯著一部等。
地 點:南海樓224數學系研習室
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2024年11月25日