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检索条件"机构=Machine-Learning and Data Analytics"
240 条 记 录,以下是191-200 订阅
排序:
Reducing over-smoothness in speech synthesis using Generative Adversarial Networks
Reducing over-smoothness in speech synthesis using Generativ...
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IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON
作者: Leyuan Sheng Evgeniy N. Pavlovskiy Novosibirsk State University Novosibirsk Russia Stream Data Analytics and Machine Learning laboratory Novosibirsk State University Novosibirsk Russia
Speech synthesis is widely used in many practical applications. In recent years, speech synthesis technology has developed rapidly. However, one of the reasons why synthetic speech is unnatural is that it often has ov... 详细信息
来源: 评论
Uncertainty Quantification in machine learning for Engineering Design and Health Prognostics: A Tutorial
arXiv
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arXiv 2023年
作者: Nemani, Venkat Biggio, Luca Huan, Xun Hu, Zhen Fink, Olga Tran, Anh Wang, Yan Zhang, Xiaoge Hu, Chao Department of Mechanical Engineering Iowa State University AmesIA50011 United States Data Analytics Lab ETH Zürich Switzerland Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States Department of Industrial and Manufacturing Systems Engineering University of Michigan-Dearborn DearbornMI48128 United States Intelligent Maintenance and Operations Systems EPFL Lausanne12309 Switzerland Scientific Machine Learning Sandia National Laboratories AlbuquerqueNM87123 United States George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Kowloon Hong Kong New Territories Hong Kong Department of Mechanical Engineering University of Connecticut StorrsCT06269 United States
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and mana... 详细信息
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Multidimensional scaling, Sammon mapping, and Isomap: Tutorial and survey
arXiv
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arXiv 2020年
作者: Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
Multidimensional Scaling (MDS) is one of the first fundamental manifold learning methods. It can be categorized into several methods, i.e., classical MDS, kernel classical MDS, metric MDS, and non-metric MDS. Sammon m... 详细信息
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Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey
arXiv
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arXiv 2020年
作者: Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
Stochastic Neighbor Embedding (SNE) is a manifold learning and dimensionality reduction method with a probabilistic approach. In SNE, every point is consider to be the neighbor of all other points with some probabilit... 详细信息
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Locally linear embedding and its variants: Tutorial and survey
arXiv
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arXiv 2020年
作者: Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science & David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada
This is a tutorial and survey paper for Locally Linear Embedding (LLE) and its variants. The idea of LLE is fitting the local structure of manifold in the embedding space. In this paper, we first cover LLE, kernel LLE... 详细信息
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Harnessing multimodal approaches for depression detection using large language models and facial expressions
Npj mental health research
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Npj mental health research 2024年 第1期3卷 66页
作者: Misha Sadeghi Robert Richer Bernhard Egger Lena Schindler-Gmelch Lydia Helene Rupp Farnaz Rahimi Matthias Berking Bjoern M Eskofier Machine Learning and Data Analytics Lab (MaD Lab) Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Erlangen 91052 Germany. misha.sadeghi@fau.de. Machine Learning and Data Analytics Lab (MaD Lab) Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Erlangen 91052 Germany. Chair of Visual Computing (LGDV) Department of Computer Science Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Erlangen 91058 Germany. Chair of Clinical Psychology and Psychotherapy (KliPs) Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Erlangen 91052 Germany. Translational Digital Health Group Institute of AI for Health Helmholtz Zentrum München - German Research Center for Environmental Health Neuherberg 85764 Germany.
Detecting depression is a critical component of mental health diagnosis, and accurate assessment is essential for effective treatment. This study introduces a novel, fully automated approach to predicting depression s...
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learning with Group Noise
arXiv
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arXiv 2021年
作者: Wang, Qizhou Yao, Jiangchao Gong, Chen Liu, Tongliang Gong, Mingming Yang, Hongxia Han, Bo Department of Computer Science Hong Kong Baptist University Hong Kong Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of MoE School of Computer Science and Engineering Nanjing University of Science and Technology China Data Analytics and Intelligence Lab Alibaba Group China Department of Computing Hong Kong Polytechnic University Hong Kong Trustworthy Machine Learning Lab School of Computer Science University of Sydney Australia School of Mathematics and Statistics University of Melbourne Australia
machine learning in the context of noise is a challenging but practical setting to plenty of real-world applications. Most of the previous approaches in this area focus on the pairwise relation (casual or correlationa... 详细信息
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Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers
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Informatics in Medicine Unlocked 2023年 42卷
作者: Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States
The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistr... 详细信息
来源: 评论
Unmasking DeepFakes with simple features
arXiv
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arXiv 2019年
作者: Durall, Ricard Keuper, Margret Pfreundt, Franz-Josef Keuper, Janis Fraunhofer ITWM Germany IWR University of Heidelberg Germany Fraunhofer Center Machine Learning Germany Data and Web Science Group University Mannheim Germany Institute for Machine Learning and Analytics Offenburg University Germany
Deep generative models have recently achieved impressive results for many real-world applications, successfully generating high-resolution and diverse samples from complex data sets. Due to this improvement, fake digi... 详细信息
来源: 评论
Assessing Personality Traits of Team Athletes in Virtual Reality
Assessing Personality Traits of Team Athletes in Virtual Rea...
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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on
作者: Markus Wirth Stefan Gradl Wolfgang A. Mehringer Richard Kulpa Hannes Rupprecht Dino Poimann Annemarie F. Laudanski Bjoern M. Eskofier Machine Learning & Data Analytics Univ. of Erlangen-Nürnberg (FAU) Erlangen Germany MM2S Lab University Rennes 2 Rennes France FC Red Bull Salzburg Academy Salzburg Austria Department of Kinesiology University of Waterloo Waterloo Ontario Canada
Assessment of personality traits is highly relevant in team sports in order to analyze the performance of an athlete under pressure when in competitive situations, for team-strategic decisions, to optimize command tra... 详细信息
来源: 评论