Results 81 to 90 of about 8,744,617 (299)

Machine Learning for Brain Disorders

, 2023
This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts.

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A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

Advanced Engineering Materials, EarlyView.
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares, Nadège Bouchonneau, Christian Jochum, Donald Radford   +3 more
wiley   +1 more source

Generative models based on point processes for financial time series simulation

, 2021
Presented online on April 7, 2021 at 12:15 p.m.Qi Wei has worked on multiband image processing as a Research Associate with Signal Processing Laboratory, University of Cambridge, UK, and as a Research Associate at Duke University, US.
Wei, Qi
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Learning Augmented Optimization: Faster, Better and Guaranteed

, 2019
Presented on November 20, 2019 at 12:15 p.m. in the Marcus Nanotechnology Building, Room 1116.Zhangyang (Atlas) Wang is an Assistant Professor of Computer Science and Engineering at Texas A&M University. Dr.
Wang, Zhangyang
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The need for open source software in machine learning [PDF]

, 2007
Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse ...
Ratsch, Gunnar, Scholkopf, Bernhard, Vincent, P., LeCun, Y, Ong, C., Rasmussen, Carl Edward, Rasmussen, CE, Rätsch, G., Bengio, S., Müller, KR, LeCunn, Yann, Muller, Klaus-Robert, Vincent , P., Pereira, Fernando, Vincent, Pascal, Bottou, Leon, Pereira, F, ,, Braun, ML, Ong, CS, Smola, A, Sonnenburg, S., Holmes, G, Bengio, S, Weston, Jason, Williamson, RC, Sonnenburg, S, Williamson, Robert C., Bottou, L., Ong, Cheng Soon, Pereira, F., Braun, M., Sonnenburg, Soren, Smola, Alexander, Holmes , G., Schölkopf, B, Holmes, Geoffrey, Braun, Mikio L., Bengio, Samy, Schölkopf, B., Rasmussen, C., Williamson, R., Rätch, G, Weston, J, Smola, A., Müller, K., Bottou, L, Weston, J., Vincent, P, LeCun, Y.   +49 more
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Active Learning and Machine Teaching for Online Learning: A Study of Attention and Labelling Cost

, 2021
Interactive Machine Learning (ML) has the potential to lower the manual labelling effort needed, as well as increase classification performance by incorporating a human-in-the loop component.
Persson, Jan A.,, Davidsson, Paul,, Agnes Tegen, Tegen, Agnes,, Paul Davidsson, Jan A. Persson   +5 more
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Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

Advanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang, Jianxiang Zhao, Zhaoqi Chen, Hao Gong, Yinsen Yan, Junlei Tao, Yong Yang   +6 more
wiley   +1 more source

ML@GT Lab presents LAB LIGHTNING TALKS 2020

, 2020
Presented online on December 4, 2020 at 2:00 p.m.Professor Ghassan AlRegib is currently a professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He is the director of the Multimedia and Sensors Lab (MSL) at
Essa, Irfan, Huo, Xiaoming, Chau, Duen Horng, Maguluri, Siva Theja, Zhang, Xiuwei, Li, Jing, Chava, Sudheer, Dovrolis, Constantine, Prakash, B. Aditya, Romberg, Justin, Pananjady, Ashwin, Xie, Yao, AlRegib, Ghassan, Cohen, Morris B., Gupta, Swati, Davenport, Mark A., Desai, Deven, Riedl, Mark O., Kira, Zsolt   +18 more
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Prediction of remaining useful life and downtime of induction motors with supervised machine learning

Applied Computer Science
This research aims to use a vibration monitoring system along with machine learning techniques to predict the downtime and Remaining Useful Life (RUL) of three-phase induction motors in the manufacturing sector.
Muhammad Dzulfiqar ANINDHITO, SUHARJITO
doaj   +1 more source

Active Learning: From Linear Classifiers to Overparameterized Neural Networks

, 2020
Presented online on October 7, 2020 at 12:15 p.m.Robert Nowak holds the Nosbusch Professorship in Engineering at the University of Wisconsin-Madison, where his research focuses on signal processing, machine learning, optimization, and statistics.Runtime:
Nowak, Robert
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