讲座信息

讲座信息

11.19 | AI Networking for Remote CV: A Use Case in Subway E-Ticketing

2024-11-19

Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of discovery. Here we show that incorporating the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts dramatically improves (up to 400%) AI prediction of future discoveries beyond those focused on resea

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08.16｜Symmetric Exponential Time Requires Near-Maximum Circuit Size

2024-08-12

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07.03 | 时间约束的极早检测 Early Detection of Temporal Constraint Violations

2024-07-01

Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of discovery. Here we show that incorporating the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts dramatically improves (up to 400%) AI prediction of future discoveries beyond those focused on resea

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01.04 | Deep Neural Networks for Big Data Analytics in CPSS

2024-01-01

Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of discovery. Here we show that incorporating the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts dramatically improves (up to 400%) AI prediction of future discoveries beyond those focused on resea

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12.12 | 计算机科学技术学院党委教工党支部联合主题党日活动——学科研究与发展探讨系列讲座第二期

2023-12-11

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12.12 | AI and Smart Sensors for Ubiquitous Healthcare: Challenges and Opportunities 加拿大皇家科学院院士、中国科学院外籍院士Jamal Deen教授谈人工智能、智慧感知与健康的挑战与未来

2023-12-11

Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of discovery. Here we show that incorporating the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts dramatically improves (up to 400%) AI prediction of future discoveries beyond those focused on resea

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12.07 | The Past, Present, and Future of Artificial Intelligence

2023-12-06

Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of discovery. Here we show that incorporating the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts dramatically improves (up to 400%) AI prediction of future discoveries beyond those focused on resea

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12.04｜大语言模型驱动的自动化日志分析

2023-12-04

视觉和语言导航是vision-and-langauge的一个比较新的研究方向，引起了计算机视觉、自然语言处理和机器人学界的广泛关注。2019年，我们通过提出第一个基准VLN任务和数据集Room-to-Room (R2R)开启了这个方向。从那时起，许多新的模型和数据集被提出，包括我们的REVERIE-真实室内环境中的远程具体化视觉参考表达。在本次报告中，我将首先展示原始的 VLN 任务和数据集，并且分别从数据和方法的角度来讨论这个方向的最新进展，同时，我将分享我们最近的两个关于使用GPT去解决视觉和语言导航的新方法。

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12.05 | Spatiotemporal Event Forecasting in Social Media

2023-11-25

视觉和语言导航是vision-and-langauge的一个比较新的研究方向，引起了计算机视觉、自然语言处理和机器人学界的广泛关注。2019年，我们通过提出第一个基准VLN任务和数据集Room-to-Room (R2R)开启了这个方向。从那时起，许多新的模型和数据集被提出，包括我们的REVERIE-真实室内环境中的远程具体化视觉参考表达。在本次报告中，我将首先展示原始的 VLN 任务和数据集，并且分别从数据和方法的角度来讨论这个方向的最新进展，同时，我将分享我们最近的两个关于使用GPT去解决视觉和语言导航的新方法。

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11.28 | 弘扬教育家精神：教有真情，育无止境

2023-11-24

视觉和语言导航是vision-and-langauge的一个比较新的研究方向，引起了计算机视觉、自然语言处理和机器人学界的广泛关注。2019年，我们通过提出第一个基准VLN任务和数据集Room-to-Room (R2R)开启了这个方向。从那时起，许多新的模型和数据集被提出，包括我们的REVERIE-真实室内环境中的远程具体化视觉参考表达。在本次报告中，我将首先展示原始的 VLN 任务和数据集，并且分别从数据和方法的角度来讨论这个方向的最新进展，同时，我将分享我们最近的两个关于使用GPT去解决视觉和语言导航的新方法。

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11.18 | 边缘数据管理：边缘问题边缘解决

2023-11-16

视觉和语言导航是vision-and-langauge的一个比较新的研究方向，引起了计算机视觉、自然语言处理和机器人学界的广泛关注。2019年，我们通过提出第一个基准VLN任务和数据集Room-to-Room (R2R)开启了这个方向。从那时起，许多新的模型和数据集被提出，包括我们的REVERIE-真实室内环境中的远程具体化视觉参考表达。在本次报告中，我将首先展示原始的 VLN 任务和数据集，并且分别从数据和方法的角度来讨论这个方向的最新进展，同时，我将分享我们最近的两个关于使用GPT去解决视觉和语言导航的新方法。

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10.23 | Robust AI for Security

2023-10-10

Artificial Intelligence is becoming more powerful than ever, e.g., GitHub Copilot suggests code to developers, and Large Language Model (LLM) Plugins will soon assist many tasks in our daily lives. We can utilize the power of AI to solve security problems, which needs to be robust against new attacks and new vulnerabilities. In this talk, I will first discuss how to develop robust AI techniques for malware detection. Our research finds that, after training an Android malware classifier on one y

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09.24 | Recent Progress on Causality in Computer Vision

2023-09-13

Causal intervention is a practical approach for achieving unbiased (debiasing) and out-of-domain (OOD) generalization in classification. In recent years of visual causality research, the construction of causal graphs has often relied heavily on the researcher's own understanding of the problem, resulting in subjectivity and controversy. This report will explore: 1) how to objectively construct causal graphs, 2) the tangible benefits that such objective causal graphs can bring, and 3) based on so

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09.24 | 视觉语言导航（Vision-and-Language Navigation）：GPT时代的新玩法

2023-09-13

视觉和语言导航是vision-and-langauge的一个比较新的研究方向，引起了计算机视觉、自然语言处理和机器人学界的广泛关注。2019年，我们通过提出第一个基准VLN任务和数据集Room-to-Room (R2R)开启了这个方向。从那时起，许多新的模型和数据集被提出，包括我们的REVERIE-真实室内环境中的远程具体化视觉参考表达。在本次报告中，我将首先展示原始的 VLN 任务和数据集，并且分别从数据和方法的角度来讨论这个方向的最新进展，同时，我将分享我们最近的两个关于使用GPT去解决视觉和语言导航的新方法。

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09.20 | 人工智能浪潮下的数据库

2023-09-13

数据爆炸式的增长使得数据库需要应对的性能压力越来越大，同时越来越复杂的应用场景要求数据库具有高度的灵活性。近些年来深度学习的兴起带来了人工智能赋能万物的浪潮，从去年开始以GPT为代表的大模型又大大激发了人们用大模型赋能万物的热情。本报告将分析机器学习和大模型对数据库的影响以及数据库对二者的支持。首先针对机器学习，本报告首先分析机器学习在解决数据库问题时的适用场景、问题抽象和相关技术进展；另一方面，本报告分析了在机器学习任务执行前、执行中和执行后数据库所起到的支持作用。其次针对大模型，本报告首先总结大模型能够应对的数据库问题，其为查询语句生成、数据库参数调优、数据生成、查询优化等问题的解决提供了新的思路，节省了在复杂场景下人力成本；另一方面，大模型在实现时的基本数据类型是向量，如何在数据库中支持大规模的向量操作是亟待解决的主要问题。总体来说，人工智能给数据库提供了更多的可能性，能够提高数据库的稳定性、可靠性和性能，降低人力成本；另一方面，数据库为人工智能任务提供了贴近数据的处理功能，在减少数据移动成本的同时提供了更加丰富的功能。

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09.11 | 【学院讲座】Prediction of Length of Stay and Discharge Disposition for Emergency Department Patients

2023-09-06

A de-identified dataset was extracted from the Electric Health Record (EHR) system at the Royal Melbourne Hospital, Melbourne, Australia. This dataset encompassed all patient visits to the Emergency Department (ED) between June 2019 and December 2022, amounting to 341,026 ED visits and involving 202,520 unique patients. The aim of this study was to develop ML models capable of predicting ED visit outcomes for adult patients at different time points. Two primary binary outcomes were defined, each

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09.06 | Accelerating Social Science with Human-Aware Artificial Intelligence

2023-09-04

Artificial intelligence (AI) models trained on published scientific findings have been used to invent valuable materials and targeted therapies, but they typically ignore the human scientists who continually alter the landscape of discovery. Here we show that incorporating the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts dramatically improves (up to 400%) AI prediction of future discoveries beyond those focused on resea

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08.25 | On the Cyber-Physical Security of Emerging AI-Enabled Autonomous Cyber-Physical Systems

2023-08-23

Recent years have witnessed a global phenomenon in the real-world development, testing, and commercialization of AI-enabled autonomous Cyber-Physical Systems (CPSs) such as autonomous driving cars, drones, and robots. These systems are rapidly revolutionizing nearly every industry today, ranging from transportation, retail, and logistics (e.g., robo-taxi, autonomous truck, delivery drones/robots), to domotics, manufacturing, construction, and healthcare. Compared to traditional computer systems,

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