Compressed Sensing and Its Applications
-15%
portes grátis
Compressed Sensing and Its Applications
Third International MATHEON Conference 2017
Caire, Giuseppe; Boche, Holger; Calderbank, Robert; Petersen, Philipp; Kutyniok, Gitta; Mathar, Rudolf
Birkhauser Verlag AG
08/2019
295
Dura
Inglês
9783319730738
15 a 20 dias
641
Descrição não disponível.
An Introduction to Compressed Sensing.- Quantized Compressed Sensing: a Survey.- On reconstructing functions from binary measurements.- Classification scheme for binary data with extensions.- Generalization Error in Deep Learning.- Deep learning for trivial inverse problems.- Oracle inequalities for local and global empirical risk minimizers.- Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation.- Reconstruction Methods in THz Single-pixel Imaging.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Compressed sensing;Compressed sensing theory and applications;Compressed sensing book;Compressed sensing introduction;Compressed sensing 2019;Deep learning compressed sensing;Deep learning book;Machine learning;Quantized compressed sensing;Signal sensing book;Generalization error machine learning;MATHEON conference;information and communication, circuits
An Introduction to Compressed Sensing.- Quantized Compressed Sensing: a Survey.- On reconstructing functions from binary measurements.- Classification scheme for binary data with extensions.- Generalization Error in Deep Learning.- Deep learning for trivial inverse problems.- Oracle inequalities for local and global empirical risk minimizers.- Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation.- Reconstruction Methods in THz Single-pixel Imaging.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Compressed sensing;Compressed sensing theory and applications;Compressed sensing book;Compressed sensing introduction;Compressed sensing 2019;Deep learning compressed sensing;Deep learning book;Machine learning;Quantized compressed sensing;Signal sensing book;Generalization error machine learning;MATHEON conference;information and communication, circuits