13 search results - page 1 / 3 » Convergence of Fixed-Point Continuation Algorithms for Matri... |
FOCM
2011
12 years 11 months ago
2011
The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding etc. As this problem is NP-hard in ...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
Standard no-internal-regret (NIR) algorithms compute a fixed point of a matrix, and hence typically require O(n3 ) run time per round of learning, where n is the dimensionality of...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this paper, we address the matrix completion problem and propose a novel algorithm based on a smoothed rank function (SRF) approximation. Among available algorithms like FPCA a...
SIAMJO
2010
13 years 3 months ago
2010
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...