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TSP
2010
13 years 2 months ago
Estimating multiple frequency-hopping signal parameters via sparse linear regression
Abstract--Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating...
Daniele Angelosante, Georgios B. Giannakis, Nichol...
CVPR
2010
IEEE
14 years 1 months ago
Anatomical Parts-Based Regression Using Non-Negative Matrix Factorization
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...
Swapna Joshi, Karthikeyan Shanmugavadivel, B.S. Ma...
ICASSP
2010
IEEE
13 years 8 months 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...
CVPR
2004
IEEE
14 years 10 months ago
3D Human Pose from Silhouettes by Relevance Vector Regression
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor pr...
Ankur Agarwal, Bill Triggs
ISDA
2009
IEEE
14 years 2 months ago
Evaluation Measures for Ordinal Regression
—Ordinal regression (OR – also known as ordinal classification) has received increasing attention in recent times, due to its importance in IR applications such as learning to...
Stefano Baccianella, Andrea Esuli, Fabrizio Sebast...