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Yang Chen: Mean-Field Game as A Framework for Many-agent Inverse Reinforcement Learning
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Dong Hao: 基于社交网络的拍卖机制设计的相关问题
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Dengji Zhao: Mechanism Design Powered by Social Interactions
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Jiamou Liu: Private data query systems and data pricing
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Xiao Liu: The Consistency of Rationality Measurement
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Xiaohui Bei: Truthful Cake Sharing
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Minming Li: Fair Scheduling for Time-dependent Resources
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Ke Shi: Almost tight [katex]\ell[/katex]-covering of [katex]\Z_n[/katex]
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Yi Zhou: Finding Large Relaxed Cliques: Theory and Practice
Speaker: Yi Zhou (University of Electronic Science and Technology of China) Host: Management School in Northwestern Polytechnical University Time: 19:00 (Time in Beijing) June 2, 2022 (Thursday) Venue: Online, Tencent Meeting: 969 244 436 Abstract: 松弛团指的是近似完全图的图结构，是图论和组合优化领域的经典模型。松弛团模型在数据挖掘，人工智能领域有着重要的应用，而如何从大规模的图中挖掘大型松弛团则是这类应用均需解决共性问题。在本次报告中，我们将从算法工程的角度来介绍松弛团挖掘问题的分析和求解。具体来说，我们将介绍松弛团问题的背景、应用并重点介绍基于分支算法的松弛团问题理论及实践。我们还将以k-plex，最密子图等松弛团为例，介绍这类问题的当前最新的优化结果。
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AAAI2022约束求解与启发式算法相关论文报告
Host: HCP (Workshop on Hard Computational Problems: Theory , Algorithms and Applications) Time: 13:00-19:00 (Time in Beijing) May 27, 2022 (Friday) Venue: Online, Tencent Meeting (ID: 267-356-071) Agenda: Title Authors Optimizing Binary Decision Diagrams with MaxSAT for classification Hao Hu, Mohamed Siala, Marie-José Huguet Encoding Multi-valued Decision Diagram Constraints as Binary Constraint Trees Ruiwei Wang,…