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ICASSP
2010
IEEE
15 years 8 hour ago
Multiple frequency-hopping signal estimation via sparse regression
Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating FH signa...
Daniele Angelosante, Georgios B. Giannakis, Nichol...
ICSM
2007
IEEE
15 years 6 months ago
Applying Interface-Contract Mutation in Regression Testing of Component-Based Software
Regression testing, which plays an important role in software maintenance, usually relies on test adequacy criteria to select and prioritize test cases. However, with the wide use...
Shan-Shan Hou, Lu Zhang, Tao Xie, Hong Mei, Jiasu ...
NCI
2004
141views Neural Networks» more  NCI 2004»
15 years 1 months ago
Estimating the error at given test input points for linear regression
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
Masashi Sugiyama
ICASSP
2011
IEEE
14 years 3 months ago
Robust nonparametric regression by controlling sparsity
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
Gonzalo Mateos, Georgios B. Giannakis
ICASSP
2011
IEEE
14 years 3 months ago
Weighted and structured sparse total least-squares for perturbed compressive sampling
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
Hao Zhu, Georgios B. Giannakis, Geert Leus