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Sparse Gaussian Process Approximations and Applications

2019
Many tasks in machine learning require learning some kind of input-output relation (function), for example, recognising handwritten digits (from image to number) or learning the motion behaviour of a dynamical system like a pendulum (from positions and velocities now to future positions and velocities).
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Sparse Target Batch-Processing Framework for Scanning Radar Superresolution Imaging

IEEE Geoscience and Remote Sensing Letters, 2023
Xingyu Tuo   +2 more
exaly  

Sparse Principal Component Analysis for Natural Language Processing

Annals of Data Science, 2020
Reza Drikvandi
exaly  

Sparse DiPCA for dynamic process monitoring

2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS), 2021
Jingxin Zhang 0002   +2 more
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A Green Prospective for Learned Post-Processing in Sparse-View Tomographic Reconstruction

Journal of Imaging, 2021
Elena Morotti   +2 more
exaly  

A Discretization-Free Sparse and Parametric Approach for Linear Array Signal Processing

IEEE Transactions on Signal Processing, 2014
Zai Yang, Lihua Xie, Cishen Zhang
exaly  

Sparse Matrix Vector Processing Formats.

2004
In this dissertation we have identified vector processing shortcomings related to the efficient storing and processing of sparse matrices. To alleviate existent problems we propose two storage formats denoted as Block Based Compression Storage (BBCS) format and Hierarchical Sparse Matrix (HiSM) storage.
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Current progress in sparse signal processing applied to radar imaging

Science China Technological Sciences, 2013
Bingchen Zhang   +2 more
exaly  

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