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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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Zibo Zhou: Two-dimensional irregular bin packing problem
Speaker: Zibo Zhou (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) April 21, 2023 (Friday) Venue: 518, Research Building 4 Abstract: We proposes a local search combined with DJD heuristic approach for the two-dimensional irregular bin packing problem (2DIBPP) with limited rotations. The objective of 2DIBPP is to pack a […]
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Multi-unit Auction over a Social Network
Speaker: Yuan Fang (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) April 14, 2023 (Friday) Venue: 518, Research Building 4 Abstract: Diffusion auction is an emerging business model where a seller aims to incentivise buyers in a social network to diffuse the auction information thereby attracting potential buyers. We focus […]
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A $(2+\epsilon)k$-vertex kernel for Edge Triangle Deletion Problem
Speaker: Yuxi Liu (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) April 7, 2023 (Friday) Venue: 518, Research Building 4 Abstract: The Edge Triangle Deletion problem asks whether we can delete at most edges from the input graph such that there is no triangle in the remaining graph. This problem […]
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Zimo Sheng: Improved Kernels for Edge Triangle Covering Problem
Speaker: Zimo Sheng (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) March 31, 2023 (Friday) Venue: 518, Research Building 4 Abstract: Kernelization is a concept of data preprocessing which is possible to derive upper and lower bounds on sizes of reduced instance. Edge Triangle Covering is an important NP-hard problem […]
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Qimu Xiao: Joint cross-cell offloading and resource allocation in the multi-cell MEC network via online learning
Speaker: Qimu Xiao (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) March 24, 2023 (Friday) Venue: 518, Research Building 4 Abstract: A widely studied typical mobile edge computing (MEC) system network consists of a cloud server, some edge servers, and some user equipment, which promises a satisfactory user experience by […]
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Dong Hao: Invitation in Contest Mechanism Design
Speaker: Dong Hao (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) March 17, 2023 (Friday) Venue: 518, Research Building 4 Abstract: In a contest, a principal holding a task posts it to a crowd. People in the crowd then compete to win the principal’s rewards. Although a crowd is usually […]
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Connectivity in the presence of an opponent
Speaker: Zihui Liang (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) March 10, 2023 (Friday) Venue: 518, Research Building 4 Abstract: We introduce two player connectivity games played on finite bipartite graphs. Algorithms that solve these connectivity games can be used as subroutines for solving M\”uller games. M\”uller games constitute […]
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Zihui Liang: Solving M¨uller Game in Polynomial Time
Speaker: Zihui Liang (University of Electronic Science and Technology of China) Time: 16:20-17:20 (Time in Beijing) March 3, 2023 (Friday) Venue: 518, Research Building 4 Abstract: We introduce Muller games. These are two player games played on finite graphs. They are used to model reactive systems that interact with enviroment. They are also used in […]
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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。