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...
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...
Image restoration problems are often converted into large-scale, nonsmooth and nonconvex optimization problems. Most existing minimization methods are not efficient for solving su...
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...
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, ...