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苏州大学计算机科学与技术学院杨壮副教授撰写的论文“Improved Powered Stochastic Optimization Algorithms for Large-Scale Machine Learning”在机器学习顶级期刊Journal of Machine Learning Research(JMLR)上在线发表,杨壮副教授为该论文的唯一作者,苏州大学计算机科学与技术学院为该论文...
Machine learning (ML) programs computers to learn the way we do—through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big da...
本报告介绍我们近期的两项工作。(1) 求解PDE的PINN方法在处理时间发展方程时往往遇到难以收敛的困难。我们发展了时间方向的预训练PINN方法及自适应步长方法,解决了收敛性困难,使PDE求解精度能够得到系统性提高。我们在一系列时间发展方程上获得了比文献报道更精确的训练结果。(2) 辐射调源问题是一个典型的反问题,要求调整辐射输运方程的边条件(源),使解满足特定设计目标。我们针对辐射输运方程的时序...
Nonlinear dynamics play a prominent role in many domains and are notoriously difficult to solve. Whereas previous quantum algorithms for general nonlinear equations have been severely limited due to t...
It’s no secret that OpenAI’s ChatGPT has some incredible capabilities — for instance, the chatbot can write poetry that resembles Shakespearean sonnets or debug code for a computer program. These abil...
In this paper we apply economic narratives to inflation forecasting using a large news corpus and machine learning algorithms. We measure economic narratives quantitatively from the full text content ...
In this talk, we present our work on structure-preserving machine learning (ML) moment closure models for the radiative transfer equation. Most of the existing ML closure models are not able to guaran...
Researchers from Brown and MIT suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequentia...
A Cornell-led collaboration used machine learning to pinpoint the most accurate means, and timelines, for anticipating the advancement of Alzheimer’s disease in people who are either cognitively norma...
Picture two teams squaring off on a football field. The players can cooperate to achieve an objective, and compete against other players with conflicting interests. That’s how the game works.
We present recent developments in double machine learning (DML) approach. The DML approach is concerned primarily with selecting the relevant control variables and functional forms necessary for the c...
Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job an...
Fusion, which promises practically unlimited, carbon-free energy using the same processes that power the sun, is at the heart of a worldwide research effort that could help mitigate climate change.
The MIT School of Engineering and Pillar VC today announced the MIT-Pillar AI Collective, a one-year pilot program funded by a gift from Pillar VC that will provide seed grants for projects in artific...
The first step in choosing the appropriate treatment for a cancer patient is to identify their specific type of cancer, including determining the primary site — the organ or part of the body where the...

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