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ESANN
2004
14 years 11 months ago
Robust overcomplete matrix recovery for sparse sources using a generalized Hough transform
We propose an algorithm for recovering the matrix A in X = AS where X is a random vector of lower dimension than S. S is assumed to be sparse in the sense that S has less nonzero e...
Fabian J. Theis, Pando G. Georgiev, Andrzej Cichoc...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
14 years 11 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
ICASSP
2009
IEEE
15 years 4 months ago
Robust-SL0 for stable sparse representation in noisy settings
In the last few years, we have witnessed an explosion in applications of sparse representation, the majority of which share the need for finding sparse solutions of underdetermine...
Armin Eftekhari, Massoud Babaie-Zadeh, Christian J...
HPCC
2005
Springer
15 years 3 months ago
Fast Sparse Matrix-Vector Multiplication by Exploiting Variable Block Structure
Abstract. We improve the performance of sparse matrix-vector multiplication (SpMV) on modern cache-based superscalar machines when the matrix structure consists of multiple, irregu...
Richard W. Vuduc, Hyun-Jin Moon
AAAI
2008
15 years 6 days ago
Sparse Projections over Graph
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
Deng Cai, Xiaofei He, Jiawei Han