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检索条件"机构=Interdisciplinary Center for Machine Learning and Data Analytics"
60 条 记 录,以下是31-40 订阅
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series data and Sequential Decision Making
arXiv
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arXiv 2023年
作者: Yu, Shujian Li, Hongming Løkse, Sigurd Jenssen, Robert Príncipe, José C. Machine Learning Group UiT - The Arctic University of Norway Tromsø Norway The Quantitative Data Analytics Group Vrije Universiteit Amsterdam Netherlands Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Drones and Autonomous Systems group NORCE Norwegian Research Centre Tromsø Norway Pioneer AI Centre Copenhagen University Denmark The Norwegian Computing Center Oslo Norway
The Cauchy-Schwarz (CS) divergence was developed by Príncipe et al. in 2000. In this paper, we extend the classic CS divergence to quantify the closeness between two conditional distributions and show that the de... 详细信息
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learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches
Learning Embeddings for Image Clustering: An Empirical Study...
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International Conference on Pattern Recognition
作者: Kalun Ho Janis Keuper Franz-Josef Pfreundt Margret Keuper Data and Web Science Group University of Mannheim Germany Institute for Machine Learning and Analytics (IMLA) Offenburg University Germany Competence Center High Performance Computing Fraunhofer ITWM Kaiserslautern Germany
In this work, we evaluate two different image clustering objectives, k-means clustering and correlation clustering, in the context of Triplet Loss induced feature space embeddings. Specifically, we train a convolution... 详细信息
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Fast machine learning Simulator of At-Sensor Radiances for Solar-Induced Fluorescence Retrieval with DESIS and Hyplant
Fast Machine Learning Simulator of At-Sensor Radiances for S...
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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)
作者: Miguel Pato Kevin Alonso Stefan Auer Jim Buffat Emiliano Carmona Stefan Maier Rupert Müller Patrick Rademske Uwe Rascher Hanno Scharr Earth Observation Center Remote Sensing Technology Institute German Aerospace Center (DLR) Germany Largo Galileo Galilei RHEA Group c/o European Space Agency (ESA) Frascati Italy Institute of Bio- and Geosciences IBG-2: Plant Sciences Forschungszentrum Jülich GmbH Julich Germany Institute of Advanced Simulations IAS-8: Data Analytics and Machine Learning Forschungszentrum Jülich GmbH Jülich Germany
In many remote sensing applications the measured radiance needs to be corrected for atmospheric effects to study surface properties such as reflectance, temperature or emission features. The correction often applies r...
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Retraction Note: Efficient user authentication protocol for distributed multimedia mobile cloud environment
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Journal of Ambient Intelligence and Humanized Computing 2024年 第1期15卷 275-275页
作者: Vivekanandan, Manojkumar Sastry, V. N. Srinivasulu Reddy, U. Center for Mobile Banking (CMB) Institute for Development and Research in Banking Technology (IDRBT) Hyderabad India Machine Learning and Data Analytics Lab Department of Computer Applications National Institute of Technology Tiruchirappalli India
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Monitoring medication optimization in patients with Parkinson’s disease
Monitoring medication optimization in patients with Parkinso...
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
作者: Hamid Moradi Julius Hannink Sabine Stallforth Till Gladow Stefan Ringbauer Martin Mayr Jürgen Winkler Jochen Klucken Bjoern M. Eskofier Department of Artificial Intelligence in Biomedical Engineering Machine Learning and Data Analytics Laboratory (MaD Lab) Friedrich Alexander University Erlangen Nuremberg Erlangen-Nuremberg Germany Portabiles HealthCare Technologies GmbH Erlangen Germany Department of Molecular-Neurology University Hospital Erlangen Erlangen Germany Medical Valley Digital Health Application Center Bamberg Germany NeuroSys GmbH Ulm Germany Luxembourg Institute of Health Centre Hospitalier du Luxembourg University of Luxembourg
Medication optimization is a common component of the treatment strategy in patients with Parkinson’s disease. As the disease progresses, it is essential to compensate for the movement deterioration in patients. Conve...
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DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
arXiv
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arXiv 2023年
作者: Ding, Lisang Jin, Kexin Ying, Bicheng Yuan, Kun Yin, Wotao Department of Mathematics University of California Los AngelesCA United States Department of Mathematics Princeton University PrincetonNJ United States Google Inc. Los AngelesCA United States Center for Machine Learning Research Peking University Beijing China AI for Science Institute Beijing China National Engineering Labratory for Big Data Analytics and Applications Beijing China Decision Intelligence Lab. Alibaba US BellevueWA United States
Decentralized Stochastic Gradient Descent (SGD) is an emerging neural network training approach that enables multiple agents to train a model collaboratively and simultaneously. Rather than using a central parameter s... 详细信息
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Latent space conditioning on generative adversarial networks
arXiv
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arXiv 2020年
作者: Lopez, Ricard Durall Ho, Kalun Pfreundt, Franz-Josef Keuper, Janis Fraunhofer ITWM Germany IWR University of Heidelberg Germany Fraunhofer Center Machine Learning Germany Data and Web Science Group University of Mannheim Germany Institute for Machine Learning and Analytics Offenburg University Germany
Generative adversarial networks are the state of the art approach towards learned synthetic image generation. Although early successes were mostly unsupervised, bit by bit, this trend has been superseded by approaches... 详细信息
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MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments (vol 18, e1010241, 2022)
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PLOS COMPUTATIONAL BIOLOGY 2022年 第9期18卷 e1010241页
作者: Alinejad-Rokny, Hamid Modegh, Rassa Ghavami Rabiee, Hamid R. Sarbandi, Ehsan Ramezani Rezaie, Narges Tam, Kin Tung Forrest, Alistair R. R. Harry Perkins Institute of Medical Research QEII Medical Centre and Centre for Medical Research The University of Western Australia Perth Australia Bio Medical Machine Learning Lab (BML) The Graduate School of Biomedical Engineering UNSW Sydney Sydney Australia Health Data Analytics Program AI-enabled Processes (AIP) Research Centre Macquarie University Sydney Australia Bioinformatics and Computational Biology Lab Department of Computer Engineering Sharif University of Technology Tehran Iran Center for Complex Biological Systems University of California Irvine Irvine California United States of America
Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction fre... 详细信息
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A Bidirectional LSTM Model for Classifying Chatbot Messages
A Bidirectional LSTM Model for Classifying Chatbot Messages
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International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)
作者: Nunthawat Lhasiw Nuttapong Sanglerdsinlapachai Tanatorn Tanantong Faculty of Science and Technology Thammasat University Pathum Thani Thailand Strategic Analytics Networks With Machine Learning and AI Research Team National Electronics and Computer Technology Center Pathum Thani Thailand Thammasat Research Unit in Data Innovation and Artificial Intelligence Faculty of Science and Technology Thammasat University Pathum Thani Thailand
Online channels, e.g., Facebook Messenger and Line, are widely used especially in COVID-19 pandemic. To quickly respond to their customer, chatbot system are implemented in many companies or organizations, connected t... 详细信息
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Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions
arXiv
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arXiv 2020年
作者: Durall, Ricard Keuper, Margret Keuper, Janis Competence Center High Performance Computing Fraunhofer ITWM Kaiserslautern Germany Data- and Webscience Group University Mannheim Germany IWR University of Heidelberg Germany Institute for Machine Learning and Analytics Offenburg University Germany
Generative convolutional deep neural networks, e.g. popular GAN architectures, are relying on convolution based up-sampling methods to produce non-scalar outputs like images or video sequences. In this paper, we show ... 详细信息
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