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SIAMJO
2008
93views more  SIAMJO 2008»
13 years 4 months ago
Smooth Optimization with Approximate Gradient
We show that the optimal complexity of Nesterov's smooth first-order optimization algorithm is preserved when the gradient is only computed up to a small, uniformly bounded er...
Alexandre d'Aspremont
IR
2010
13 years 3 months ago
Gradient descent optimization of smoothed information retrieval metrics
Abstract Most ranking algorithms are based on the optimization of some loss functions, such as the pairwise loss. However, these loss functions are often different from the criter...
Olivier Chapelle, Mingrui Wu
SIAMIS
2010
155views more  SIAMIS 2010»
12 years 11 months ago
Smoothing Nonlinear Conjugate Gradient Method for Image Restoration Using Nonsmooth Nonconvex Minimization
Image restoration problems are often converted into large-scale, nonsmooth and nonconvex optimization problems. Most existing minimization methods are not efficient for solving su...
Xiaojun Chen, Weijun Zhou
GECCO
2010
Springer
211views Optimization» more  GECCO 2010»
13 years 5 months ago
Investigating EA solutions for approximate KKT conditions in smooth problems
Evolutionary algorithms (EAs) are increasingly being applied to solve real-parameter optimization problems due to their flexibility in handling complexities such as non-convexity,...
Rupesh Tulshyan, Ramnik Arora, Kalyanmoy Deb, Joyd...
SIAMIS
2011
12 years 11 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang