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JMLR
2012
13 years 4 months ago
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
TASLP
2010
78views more  TASLP 2010»
14 years 8 months ago
Solving Demodulation as an Optimization Problem
We introduce two new methods for the demodulation of acoustic signals by posing the problem in a convex optimization framework. This allows the parameters of the modulator and carr...
Gregory Sell, Malcolm Slaney
SIAMJO
2000
88views more  SIAMJO 2000»
15 years 1 months ago
A Feasible BFGS Interior Point Algorithm for Solving Convex Minimization Problems
Abstract. We propose a BFGS primal-dual interior point method for minimizing a convex function on a convex set defined by equality and inequality constraints. The algorithm generat...
Paul Armand, Jean Charles Gilbert, Sophie Jan-J&ea...
CDC
2008
IEEE
124views Control Systems» more  CDC 2008»
15 years 8 months ago
A proximal center-based decomposition method for multi-agent convex optimization
— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...
Ion Necoara, Johan A. K. Suykens
ALGORITHMICA
2006
93views more  ALGORITHMICA 2006»
15 years 2 months ago
Simultaneous Optimization via Approximate Majorization for Concave Profits or Convex Costs
For multi-criteria problems and problems with poorly characterized objective, it is often desirable to simultaneously approximate the optimum solution for a large class of objecti...
Ashish Goel, Adam Meyerson