专家预测最准确的篮球

讲座信息

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

2023-11-30

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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08.13 | When Artificial Intelligence Meets Networking and vice versa

2023-08-07

Artificial Intelligence (AI) is one of the most influential technologies today, with wide applications in various fields such as autonomous driving and intelligent surveillance systems. As AI technology continues to advance, there is great anticipation for its potential and creativity in applications. Multi-agent cooperation, also known as collective intelligence or collaborative intelligence, has become a significant focus for future development. Through collaboration, the capabilities of multi

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08.13 | 快速迭代的云网络系统设计与应用

2023-08-06

在大规模分布式系统中，网络系统是影响应用性能、可用性和稳定性的关键组件。云网络系统作为云计算的重要基础设施，支撑包括存储、计算在内的多种多样的业务。因为云计算服务快速发展的需求，云网络系统需要具备快速功能迭代的特性。我们的报告将介绍实现快速迭代的云数据中心和云网络的一些主要问题和解决思路，包括通过软硬件融合的方式支持数据中心RDMA低延迟、高吞吐、节省CPU网络传输；软件架构消除异构设备的配置和性能差距，支撑异构硬件混合互联；快速高效的业务上线系统参数配置，支持灵活卸载的可靠性、拥塞控制等网络功能模块部署, 以及如何实现跨域、多数据中心业务互联来支撑未来算力网络。

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08.11 | What are language agents and why should we study them?

2023-08-05

A recent focus in AI is autonomous agents, which, usually powered by large language models (LLMs), can follow language instructions to autonomously carry out complex tasks in real-world environments. However, the concept of agent has been introduced into AI since its dawn, so what's different this time around? I argue that the most fundamental change is the capability of using language. Contemporary AI agents use language as a vehicle for both communication and thought, which enables them to do

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08.10 | 数字健康技术新进展 New Advances in Digital Health for Improving Healthcare

2023-08-03

近年来，现代化"数字健康"在数据科学领域取得了长足进步，为改善患者护理提供了许多机会。本讲座将全景式介绍现代医疗健康技术的发展现状与前景，并列举牛津大学在开发改善患者生活的医疗健康干预措施方面的研究实例。

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08.01 | Open-World Streaming Algorithms: Paradigm, Challenge, and Prospect 开放世界流处理算法：范式、挑战与展望

2023-07-26

Machine learning (ML) strives to build mathematical models that uncover and mimic the hidden decision-making process of human minds in a data-driven fashion. Despite its popularity and successes in many industrial and scientific endeavors, a fundamental difference lying between the learning environments of ML models and human-beings hinders the widespread application of ML in real tasks. To wit, we humans live in an evolving world so must keep adjusting and reshaping our mental process to accomm

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07.18 | Object-Centric Perception for Robot Manipulation

2023-07-11

One of the core problems in robot manipulation is enabling robots to manipulate objects and use objects to perform tasks. Compared to end-to-end approaches that take sensory input and output control commands, I believe enabling robots to understand objects from sensory input and conditioning planning and control on top of object perception can achieve generalizable robot manipulation. In this talk, I will highlight our efforts on object-centric perception for robot manipulation. I will start wit

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