His primary areas of investigation include Algorithm, Iterative method, Artificial intelligence, Sampling and Computer vision. His Algorithm research is multidisciplinary, incorporating elements of Signal reconstruction, Signal processing, Filter, Iterative reconstruction and Autocorrelation. His research integrates issues of Robust principal component analysis, Fixed point and Maxima and minima in his study of Iterative method.
Yue M. Lu has researched Artificial intelligence in several fields, including Filter bank and Bilinear interpolation. His Sampling study combines topics from a wide range of disciplines, such as Mathematical optimization, Linear subspace and Oversampling. His research in Computer vision intersects with topics in Nearest-neighbor interpolation, Stairstep interpolation and Linear interpolation.
Yue M. Lu focuses on Algorithm, Artificial intelligence, Mathematical optimization, Applied mathematics and Computer vision. His work deals with themes such as Sampling, Phase retrieval, Fourier transform and Iterative reconstruction, which intersect with Algorithm. His studies in Artificial intelligence integrate themes in fields like Computer graphics and Pattern recognition.
His work in the fields of Mathematical optimization, such as Iterative method, intersects with other areas such as Electric power system. His study in Applied mathematics is interdisciplinary in nature, drawing from both Dimension, Regularization, Sequence and Limit. The Computer vision study combines topics in areas such as Color filter array and Near-infrared spectroscopy.
Yue M. Lu spends much of his time researching Applied mathematics, Regularization, Limit, Dimension and Generalization. Yue M. Lu undertakes interdisciplinary study in the fields of Applied mathematics and Universality through his works. Yue M. Lu interconnects Artificial neural network, Perceptron, Asymptotic analysis and Convex optimization, Regular polygon in the investigation of issues within Regularization.
His Regular polygon research incorporates elements of Function, Feature, Activation function and Interpolation. He combines subjects such as Computational complexity theory, Spectral gap, Phase retrieval, Hypersphere and Uniform distribution with his study of Limit. He connects Phase retrieval with Generative model in his research.
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Supervised and Traditional Term Weighting Methods for Automatic Text Categorization
Man Lan;Chew Lim Tan;Jian Su;Yue Lu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)
An Algorithm for License Plate Recognition Applied to Intelligent Transportation System
Ying Wen;Yue Lu;Jingqi Yan;Zhenyu Zhou.
IEEE Transactions on Intelligent Transportation Systems (2011)
A Theory for Sampling Signals From a Union of Subspaces
Y.M. Lu;M.N. Do.
IEEE Transactions on Signal Processing (2008)
Multidimensional Directional Filter Banks and Surfacelets
Y.M. Lu;M.N. Do.
IEEE Transactions on Image Processing (2007)
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
Yuejie Chi;Yue M. Lu;Yuxin Chen.
IEEE Transactions on Signal Processing (2019)
A New Contourlet Transform with Sharp Frequency Localization
Y. Lu;M. N. Do.
international conference on image processing (2006)
Acoustic echoes reveal room shape
Ivan Dokmanić;Reza Parhizkar;Andreas Walther;Yue M. Lu.
Proceedings of the National Academy of Sciences of the United States of America (2013)
A Spectral Graph Uncertainty Principle
A. Agaskar;Y. M. Lu.
IEEE Transactions on Information Theory (2013)
CRISP contourlets: a critically sampled directional multiresolution image representation
Yue Lu;Minh N. Do.
Proceedings of SPIE - The International Society for Optical Engineering (2003)
Cytokines and Behcet's disease.
Z.Y. Zhou;S.L. Chen;N. Shen;N. Shen;N. Shen;Y. Lu.
Autoimmunity Reviews (2012)
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