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11-26
2025
兼顾速度与质量的关系聚类：Mikkel Thorup教授特邀学术讲座
2025年11月24日，丹麦皇家科学和文学院院士、丹麦哥本哈根大学教授Mikkel Thorup做客熟女 交叉信息院，带来题为“兼顾速度与质量的关系聚类（Fast and Good Correlation Clustering）”特邀报告。交叉信息院副教授段然主持讲座。师生齐聚FIT楼1-222会议室，聆听讲座。关系聚类（Correlation Clustering ）是一个在图论、机器学习和数据挖掘中有很多应用的重要问题。但其精确求解是 NP 难的，因此研究重点长期聚焦于近似算...
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11-24
2025
Fast and Good Correlation Clustering
演讲人：Mikkel Thorup [University of Copenhage]时间：14:00-15:00, Nov 24, 2025 (Mon)地点：RM 1-222, FIT Building内容：A clustering is a partitioning into sets called clusters. The input to (unweighted) correlation clustering is an unweighted graph. We want to cluster the vertices so as to minimimize the number of edges between clusters plus the number of non-edges inside clusters.Recently there...
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11-07
2025
Beyond ASICs: GPU-Accelerated FHE and Evolving LLM Strategies on Programmable Hardware
演讲人：Jung Ho Ahn [首尔国立大学] 时间：10:00-11:00, Nov 7, 2025 (Fri)地点：RM 1-222, FIT Building内容：GPUs continue to redefine performance boundaries across diverse workloads. This talk presents two compelling examples from our latest research, underscoring the critical role of programmable accelerators. First, we demonstrate how our group surpassed DARPA's ambitious 2021 DPRIVE ASIC target...
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11-06
2025
LLM theory for training wireless networks
演讲人：Lingjie Duan [SUTD]时间：14:00-15:00, Nov 6, 2025 (Thu)地点：FIT1-312内容：Existing AI methods (model-based optimization, deep reinforcement Learning) struggle with generalization and rapid adaptation in dynamic wireless networks. This work pioneers "LLM for Wireless," harnessing the general intelligence of Large Language Models (LLMs) to proactively optimize network infrastructure, mov...
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10-28
2025
Majorana zero modes and topological quantum computing based on Meissner effect and Abrikosov vortex
演讲人：刘鑫 [华中科技大学]时间：16:00-17:00, Oct 28, 2025 (Tue)地点：RM S327, MMW Building内容：Majorana zero modes (MZMs) exhibit non-Abelian braiding statistics, rendering them a cornerstone for topological quantum computing. A robust MZM platform demands a wide topological superconducting parameter space that facilitates experimental detection and control of MZMs and provides a promising de...
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10-24
2025
泛函尺度律：大模型尺度现象的动力学解释
演讲人： 吴磊 【北京大学】时间：14:00-15:00, Oct 24, 2025 (Tue)地点：吕大龙楼701会议室内容：大模型尺度律揭示：性能随训练数据规模和计算量的增长呈现出可预测的幂律提升。这一规律深刻推动了现代人工智能的发展，但长期停留在经验观察层面，缺乏理论理解。为探究其成因，我们引入幂律核回归（power-law kernel regression）这一简化模型，作为理论原型来抽象尺度现象的关键机制。基于该模型的动力学推导，我们提出泛函尺...