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Yan Gu:Recent Advances in Parallel Algorithm Design
Speaker: Yan Gu(University of California, Riverside) Time: 16:20-17:20 (Time in Beijing) September 8, 2023 (Friday) Venue: 518, Research Building 4 Abstract: This talk will cover some new advances in recent parallel algorithm research. We will introduce a few new parallel algorithms on classic graph problems such as single-source shortest paths (the rho-stepping and the delta*-stepping […]
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Yan Gu:Introduction to Parallel Algorithms
Speaker: Yan Gu(University of California, Riverside) Time: 10:20-11:20 (Time in Beijing) September 8, 2023 (Friday) Venue: 518, Research Building 4 Abstract: Parallel processors are ubiquitous nowadays and it is almost impossible to find a single-core processor, probably other than a toaster. However, very few courses and online materials cover the basic knowledge for designing parallel […]
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Yiding Feng: Mobility Data in Operations: The Facility Location Problem
Speaker: Yiding Feng(University of Chicago) Time: 11:00-12:00 (Time in Beijing) August 4, 2023 (Friday) Venue: 518, Research Building 4 Abstract: Speaker Bio: Yiding Feng is a postdoctoral principal researcher at the University of Chicago Booth School of Business. Previously, he worked as a postdoctoral researcher at Microsoft Research New England from 2021 to 2023. He […]
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Louxin Zhang: A Scalable Algorithm for Inferring Phylogenetic Networks from Trees
Speaker: Louxin Zhang (新加坡国立大学) Time: July 3, 2023 (Monday) 10:30-11:30am Venue: 电子科技大学清水河校区主楼B1-501 Abstract: Phylogenetic networks are rooted, acyclic directed graph in which leaves are labelled with genes, genomes or species. They are used to model evolution with reticulate events. The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, […]
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Yixin Cao: Enumerating Maximal Induced Subgraphs
Speaker: 操宜新 (香港城市大学) Time: 15:00-16:00 (Time in Beijing) May 15, 2023 (Thursday) Venue: 电子科技大学清水河校区四号科研楼A区518 Abstract: Given a graph $G$, the maximal induced subgraphs problem asks to enumerate all maximal induced subgraphs of $G$ that belong to a certain hereditary graph class. While its optimization version, known as the minimum vertex deletion problem in literature, has […]
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Minming Li: Defending with Shared Resources on a Network
Speaker: 李閩溟 (香港城市大学) Time: 14:00-15:00 (Time in Beijing) May 15, 2023 (Thursday) Venue: 电子科技大学清水河校区四号科研楼A区518 Abstract: In this paper we consider a defending problem on a network. In the model, the defender holds a total defending resource of R, which can be distributed to the nodes of the network. The defending resource allocated to a node […]
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Xiaohui Bei: Auction Design: from Theory to Practice
Speaker: 贝小辉 (新加坡南洋理工大学) Time: 16:20-17:20 (Time in Beijing) May 11, 2023 (Thursday) Venue: 电子科技大学清水河校区四号科研楼A区518 Abstract: As a means to facilitate efficient resource allocation, auctions are a fundamental tool in the modern economy and play a pivotal role in mechanism design theory. This talk will provide a brief introduction to auction design. We will discuss fundamental […]
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Zhiguo Fu: 平面图上计数问题的计算复杂性分类
Speaker: 付治国 (东北师范大学) Time: 11:00-12:00 (Time in Beijing) May 8, 2023 (Monday) Venue: 电子科技大学清水河校区四号科研楼A区518 Abstract: 平面图上计数问题的计算复杂性分类探索特定框架下的计数问题是否分为如下的三类:(1)一般图上可解的问题;(2)一般图上#P-难,但在平面图上可解的问题;(3)在平面图上#P-难的问题。其中一个重要的问题是基于匹配门的全息算法对(2)中的问题是否具有通用性。本报告将介绍平面图上计数问题计算复杂性分类的进展,尤其将介绍基于匹配门的全息算法与(2)中问题的关系。 Speaker Bio: 付治国,东北师范大学信息科学与技术学院教授,博士生导师,副院长。博士毕业于吉林大学数学学院计算数学专业,美国威斯康星大学麦迪逊分校博士后。研究领域为计数问题的算法与计算复杂性,成果发表在STOC,FOCS, SODA,Information and Computation等理论计算机顶级会议和期刊。
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Zeyu Zhang: RSGNN: A Model-agnostic Approach for Enhancing the Robustness of Signed Graph Neural Networks
Speaker: 张泽宇 (奥克兰大学) Time: 16:20-17:20 (Time in Beijing) April 28, 2023 (Friday) Venue: 电子科技大学清水河校区四号科研楼A区518 Abstract: Signed graphs model complex relations using both positive and negative edges. Signed graph neural networks (SGNN) are powerful tools to analyze signed graphs. We address the vulnerability of SGNN to potential edge noise in the input graph. Our goal is […]
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Zhanghua Fu: 多机器人协同调度以及运筹优化方法的产业化应用
Speaker: 付樟华 (香港中文大学深圳) Time: 15:00-16:00 (Time in Beijing) February 27, 2023 (Monday) Venue: 电子科技大学清水河校区四号科研楼A区518 Abstract: 产业界(工厂、仓储、港口、矿山、物流等)面临大量复杂的运筹优化问题,如何高效地解决这些问题,是相关企业的核心能力之一。然而,实际业务一般非常复杂,而且随着时间迅速变化,数据收集也往往相当困难,且存在误差。因此,学术界常用的优化方法往往难以直接应用于产业界。如何跨越学术研究与产业应用之间的鸿沟,成为许多运筹优化研究者所面临的问题。 Speaker Bio: 付樟华,本硕博均毕业于华中科技大学,2012年至2015年留学法国从事博士后研究。2015年回国后担任香港中文大学(深圳)以及深圳市人工智能与机器人研究院研究员,主要从事人工智能与机器人相关研究。曾于2014年12月夺得运筹优化领域著名的国际竞赛-第11届DIMACS国际算法设计大赛的冠军(华人首冠)。2016年入选深圳市“孔雀计划”海外高层次人才。2022年参与华为珠峰计划,帮助华为解决实际业务中的核心难题,获得华为颁发的“难题火花奖”。目前专注于机器人及人工智能领域相关产业化工作,已服务近十家行业龙头企业。