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ICASSP
2011
IEEE
14 years 9 months ago
Revisiting adaptive least-squares estimation and application to online sparse signal recovery
This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...
Konstantinos Slavakis, Yannis Kopsinis, Sergios Th...
SIAMJO
2011
15 years 25 days ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
SODA
2008
ACM
184views Algorithms» more  SODA 2008»
15 years 7 months ago
Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm
The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...
Kenneth L. Clarkson
EMMCVPR
2005
Springer
15 years 11 months ago
Reverse-Convex Programming for Sparse Image Codes
Abstract. Reverse-convex programming (RCP) concerns global optimization of a specific class of non-convex optimization problems. We show that a recently proposed model for sparse ...
Matthias Heiler, Christoph Schnörr
PARA
2004
Springer
15 years 11 months ago
Parallel Algorithms for Balanced Truncation Model Reduction of Sparse Systems
We describe the parallelization of an efficient algorithm for balanced truncation that allows to reduce models with state-space dimension up to O(105 ). The major computational tas...
José M. Badía, Peter Benner, Rafael ...