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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...
The analysis of data stored in multiple sites has become more popular, raising new concerns about the security of data storage and communication. Federated learning, which does not require centralizin...
近期,深圳大学医学部生物医学工程学院汪天富、雷柏英教授团队的研究成果《MHW-GAN: Multi-discriminator Hierarchical Wavelet Generative Adversarial Network for Multi-modal Image Fusion》在顶级期刊IEEE Transactions on Neural Networks and Learning ...
近日,医学部生物医学工程学院汪天富教授团队在人工智能领域顶级国际期刊《IEEE Transactions on Neural Networks and Learning Systems》(中科院大类一区,TOP期刊,IF:14.255)上发表了系列研究成果。
Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-...
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...
Maybe you can’t tell a book from its cover, but according to researchers at MIT you may now be able to do the equivalent for materials of all sorts, from an airplane part to a medical implant. Their n...
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...
2023年3月24日上午,IEEE Fellow、美国奥本大学Shiwen Mao教授应邀来南京邮电大学通信与信息工程学院作“Deep Learning for WiFi-based Indoor Fingerprinting”专题报告。本次专题报告详细地介绍了室内定位的相关内容,为南京邮电大学通信与信息工程学院师生的相关科研工作开拓了新思路。本次报告由通信与信息工程学院周亮院长主持,学院逾三百名...
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...
This report consists of two parts associated with graph neural networks: generalization and graph structural learning. We first study the Rademacher complexity of GNNs, as one of independent-algorithm...
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...
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...

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