Results 41 to 50 of about 20,444,531 (305)
Sparsity and morphological diversity for hyperspectral data analysis [PDF]
, 2010 Recently morphological diversity and sparsity have emerged as new and effective sources of diversity for Blind Source Separation. Based on these new concepts, novelmethods such as Generalized Morphological Component Analysis have been put forward ...
Bobin, J. +3 more
core +1 more source
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning [PDF]
International Symposium on High-Performance Computer Architecture, 2020 The attention mechanism is becoming increasingly popular in Natural Language Processing (NLP) applications, showing superior performance than convolutional and recurrent architectures.
Hanrui Wang, Zhekai Zhang, Song Han
semanticscholar +1 more source
An efficient sparse conjugate gradient solver using a Beneš permutation network [PDF]
, 2014 © 2014 Technical University of Munich (TUM).The conjugate gradient (CG) is one of the most widely used iterative methods for solving systems of linear equations.
Burovskiy, PA +3 more
core +1 more source
Adaptive Sparse Gaussian Process
IEEE Transactions on Neural Networks and Learning SystemsAdaptive learning is necessary for non-stationary environments where the learning machine needs to forget past data distribution. Efficient algorithms require a compact model update to not grow in computational burden with the incoming data and with the lowest possible computational cost for online parameter updating.
Vanessa Gómez-Verdejo +2 more
openaire +4 more sources
Sparse within Sparse Gaussian Processes using Neighbor Information
, 2020 10 ...
Tran, Gia-Lac +3 more
openaire +2 more sources
A Connectedness Constraint for Learning Sparse Graphs
, 2017 Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing.
friedman +8 more
core +1 more source
Sparse Multiscale Patches for Image Processing [PDF]
, 2009 This paper presents a framework to define an objective measure of the similarity (or dissimilarity) between two images for image processing. The problem is twofold: 1) define a set of features that capture the information contained in the image relevant for the given task and 2) define a similarity measure in this feature space.
Piro, Paolo +3 more
openaire +2 more sources
Leida xuebao, 2018 This paper examines the processing of millimeter-wave imaging data based on sparse sampling and sparse array design for the rapid imaging of human security data.
Tian He, Li Daojing, Qi Chunchao
doaj +1 more source
Compressed Multi-Row Storage Format for Sparse Matrices on Graphics Processing Units
, 2014 A new format for storing sparse matrices is proposed for efficient sparse matrix-vector (SpMV) product calculation on modern graphics processing units (GPUs).
Koza, Zbigniew +3 more
core +1 more source
A Review of Radar Signal Processing Based on Sparse Recovery
Leida xuebaoWith the growing demand for radar target detection, Sparse Recovery (SR) technology based on the Compressive Sensing (CS) model has been widely used in radar signal processing.
Yinghui QUAN +6 more
doaj +1 more source