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On the reals weakly low for K
Speaker: Liang Yu(professor in Nanjing University) Time: 15:00-16:00 (Time in Beijing) 20:00-21:00 (Time in Auckland) November 01, 2021 (Monday) Venue: B1-518B, Research Building 4 Abstract: Given an infinite set , real is called weakly low for on if there are infinitely many so that does not improve the prefix-free complexity of up to a constant. […]
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Quasi-Isometric Graph-Simplifications
Speaker: Roger Su(University of Auckland) Time: 10:00-12:00 (Time in Beijing) 15:00-17:00 (Time in Auckland) October 29, 2021 (Friday) Venue: Qingshuihe Campus Abstract: Quasi-isometries are a concept originally used to study infinite algebraic objects. Here we apply quasi-isometries to finite graphs, and propose a theoretical framework for simplifying large-scale graphs. This framework consists of several goals, […]
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Subset Feedback Vertex Set in Chordal Graph
Speaker: Tian Bai(University of Electronic and Science Technology of China) Time: 10:00-12:00 (Time in Beijing) 14:00-16:00 (Time in Auckland) October 15, 2021 (Friday) Venue: Qingshuihe Campus Abstract: The Subset Feedback Vertex Set (SFVS) problem takes as input a graph and a subset of vertices in . The task is to find a minimal set of […]
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Randomness and Complexity
Speaker: Cristian Calude(professor in University of Auckland) Time: 14:00-15:00 (Time in Beijing) 18:00-19:00 (Time in Auckland) October 11, 2021 (Monday) Venue: Zoom Meeting ID: 711 8843 8437 Password: 202101 Abstract: Since ancient times randomness had been viewed as an obstacle and difficulty. This attitude has changed in the last century when randomness became central to […]
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Rapid mixing of Glauber dynamics via spectral independence for all degrees
Speaker: Weiming Feng(research associate in University of Edinburgh) Time: 11:00-12:00 (Time in Beijing) 15:00-16:00 (Time in Auckland) September 17, 2021 (Friday) Venue: B1-518B, Research Building 4 Abstract: We prove an optimal lower bound on spectral gap of the Glauber dynamics for anti-ferromagnetic two-spin systems with vertices in the tree uniqueness regime. This spectral gap holds […]
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On 1-2-3 Conjecture
Speaker: Xuding Zhu(Zhejiang Normal University) Host: Shanghai Center For Mathematical Science Time: 14:00 – 16:00 (Time in Beijing) September 13, 2021 (Monday) Venue: Zoom meeting ID: 818 0564 1942 Password: 121323 Link: https://zoom.com.cn/j/81805641942 Abstract: The well-known 1-2-3 conjecture asserts that any graph with no isolated edges has an edge-weighting vertex colouring using weights 1,2 and […]
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Approximation Algorithms for TTP-3
Speaker: Jingyang Zhao(University of Electronic and Science Technology of China) Time: 10:00-12:00 (Time in Beijing) 14:00-16:00 (Time in Auckland) September 10, 2021 (Friday) VooVmeeting: Link: https://meeting.tencent.com/dm/xKZlIrcZhk0Z ID: 704 420 285 Venue: Qingshuihe Campus Abstract: The Traveling Tournament Problem is a complex combinatorial optimization problem in tournament timetabling, which asks us to design a double round-robin […]
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Heuristic Algorithms for Steiner Tree Problem
Speaker: Xinyu Wu (University of Electronic and Science Technology of China) Time: 10:00-11:00 (Time in Beijing) 14:00-15:00 (Time in Auckland) September 3, 2021 (Friday) VooVmeeting: Link: https://meeting.tencent.com/dm/WlulUnrGJ0NM?rs=25 ID: 969 615 091 Venue: Qingshuihe Campus Abstract: The Steiner tree problem (STP) is a challenging NP-hard problem that commonly arises in practical applications as one of many […]
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Sparse Metric Repair and Distance Realease
Speaker: Chenglin Fan(Ph.D UT Dallas) Time: 09:00-10:00 (Time in Beijing) 13:00-14:00 (Time in Auckland) July 30, 2021 (Friday) Venue: VooV Meeting ID: 747 545 809 Abstract: Metric data plays an important role in various settings, for example, in metric-based indexing, clustering, classification, and approximation algorithms in general. Often such tasks require the data to be […]
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面向多租户分布式机器学习的聚合传输协议
Speaker: Wenfei Wu(Tsinghua University) Time: 11:00-12:00 (Time in Beijing) 15:00-16:00 (Time in Auckland) July 16, 2021 (Friday) Venue: B1-501, Main Building Abstract: 随着机器学习数据集和模型的增大，机器学习的训练过程逐步被分布式部署到多服务器上，其中多worker向参数服务器PS交换梯度、更新模型的计算方式是一种典型的体系结构。但是，在这种体系结构下，PS容易成为通信瓶颈。我们设计了聚合传输协议ATP来解决这一瓶颈，同时支持在数据中心中的多租户多机柜部署。ATP利用最近的可编程交换机技术，将参数聚合的过程卸载到交换机上，从而减小了PS的网络流量和计算量。ATP协议包括交换机上的网内聚合计算服务、终端服务器的可靠传输、和高吞吐网卡的加速技术。我们将ATP对接PyTorch并在AlexNet、VGG等常用模型上进行测试，证明ATP能够有效的加速机器学习的效率。 Speaker Bio: 吴文斐，清华大学任助理教授。2015年博士毕业于美国威斯康星大学麦迪逊分校，后在惠普实验室任博士后研究院。2017年加入清华大学工作至今。SIGCOMM、NSDI、INFOCOM等网络顶级会议上发表论文30余篇，拥有美国专利3项。获SoCC13最佳学生论文、IPCCC最佳论文提名。 Download poster