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HYBRID
2007
Springer
14 years 3 months ago
Approximation of the Joint Spectral Radius of a Set of Matrices Using Sum of Squares
We provide an asymptotically tight, computationally efficient approximation of the joint spectral radius of a set of matrices using sum of squares (SOS) programming. The approach i...
Pablo A. Parrilo, Ali Jadbabaie
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
13 years 10 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
KDD
2008
ACM
192views Data Mining» more  KDD 2008»
14 years 9 months ago
Partial least squares regression for graph mining
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...
Hiroto Saigo, Koji Tsuda, Nicole Krämer
ICASSP
2009
IEEE
14 years 3 months ago
Analyzing Least Squares and Kalman Filtered Compressed Sensing
In recent work, we studied the problem of causally reconstructing time sequences of spatially sparse signals, with unknown and slow time-varying sparsity patterns, from a limited ...
Namrata Vaswani
IWANN
2009
Springer
14 years 3 months ago
Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...