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Communication compression is an essential strategy for alleviating communication overhead by reducing the volume of information exchanged between computing nodes in large-scale distributed stochastic ...
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...
High-dimensional sampling problems are ubiquitous in statistics, operations research, machine learning, etc. In this talk, I will introduce quantum algorithms for two important problems in high-dimens...
We consider numerical approximations of the anisotropic phase-field dendritic crystal growth model. This is a highly complex coupled nonlinear system consisting of the anisotropic Allen-Cahn equation,...
Modern neural networks are usually over-parameterized—the number of parameters exceeds the number of training data. In this case the loss functions tend to have many (or even infinite) global minima, ...
System optimization and control have become the key design philosophies in modern control system theories, where reinforcement learning (RL) algorithm has drawn considerable attention in recent litera...
Algorithms developed in Cornell’s Laboratory for Intelligent Systems and Controls can predict the in-game actions of volleyball players with more than 80% accuracy, and now the lab is collaborating wi...
2022年6月17日下午,国家级人才称号获得者,清华大学殷柳国教授来中北大学信息与通信工程学院作“Generalized Sparse Codes for Non-Gaussian Channels: Code Design,Algorithms, and Applications”专题报告。本次专题报告是南邮80周年校庆之际通信与信息工程学院举办的第10次“通院学术大讲堂”校庆系列报告会。本次报...

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