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ICASSP
2011
IEEE
12 years 11 months ago
Multi-channel EEG compression based on matrix and tensor decompositions
Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several...
Justin Dauwels, K. Srinivasan, M. Ramasubba Reddy,...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 9 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...
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 8 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
TCS
2011
13 years 2 months ago
Dynamic normal forms and dynamic characteristic polynomial
Abstract. We present the first fully dynamic algorithm for computing the characteristic polynomial of a matrix. In the generic symmetric case our algorithm supports rank-one updat...
Gudmund Skovbjerg Frandsen, Piotr Sankowski