Notice：
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03-16
2026
Generative Social Choice
演讲人：Ariel Procaccia [Harvard University] 时间：09:45-12:30, Mar 16, 2026 (Mon)地点： Lecture Hall, FIT Building内容：How should one design collective decision-making processes capable of handling enormous sets of alternatives like all possible policies, bills, or statements? I argue that this challenge can be addressed through a framework called generative social choice, which fuses the rig...
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02-28
2026
Scaling Trust without Trusting
演讲人：Binyi Chen时间：14:00-15:00, Feb 28, 2026 (Sat)地点： RM 1-222, FIT Building内容：In an era of AI and digitalization, we face a dual challenge in building trust while preserving privacy. For example, social platforms are flooded with unverifiable AI-generated content, and online services require users to excessively expose their personal data. Zero-Knowledge Succinct Proofs (ZK-SNARKs) ...
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02-27
2026
Benchmarking and fidelity response theory of high-fidelity Rydberg gates
演讲人：孙向恺 [Caltech] 时间：10:00-12:00, Feb 27, 2026 (Fri)地点： Lecture Hall, FIT Building内容：The fidelity of entangling operations is a key figure of merit in quantum information processing, especially in the context of quantum error correction. High-fidelity entangling gates in neutral atom arrays have seen remarkable advancement recently. A full understanding of error sources and thei...
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12-26
2025
Rationality of multi-agent learning and uncertainty quantification for the generative models
演讲人：Yian Ma (马易安) [University of California, San Diego]时间：13:30-15:00, Dec 26, 2025 (Fri)地点：RM 1-222, FIT Building内容：In the first part of the talk, I will discuss an interesting phenomenon in multiagent learning, that the mixed Nash equilibria are uniformly stable if and only if they are collectively rational. This justifies the effusive use of multi-agent learning systems and r...
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12-23
2025
祖冲之三超导量子计算进展
演讲人：龚明 [中国科学技术大学微尺度国家研究中心] 时间：15:00-17:30, Dec 23, 2025 (Tue)地点：RM S327, MMW Building内容：超导量子计算技术发展的核心目标是通过提升量子比特数目及操控质量，实现通用容错量子计算机。其实现路径上有三个重要的里程碑，分别是量子计算优越性、专用量子模拟、以及通用量子计算。本团队在2021年实现了量子优越性的里程碑，展示了超越经典计算的能力，为探索量子增强的近期应用提供了更多机...
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12-23
2025
Pointwise Generalization in Deep Neural Networks
演讲人：Yunbei Xu [NUS]时间：11:00-12:00, Dec 23, 2025 (Tue)地点：RM 1-222, FIT Building内容：We address the fundamental question of why deep neural networks generalize by establishing a pointwise generalization theory for fully connected networks. This framework resolves long-standing barriers to characterizing the rich, nonlinear feature-learning regime and builds a new statistical foundation...