Sciweavers

MP
2016
10 years 3 months ago
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm
We improve a recent guarantee of Bach and Moulines on the linear convergence of SGD for smooth and strongly convex objectives, reducing a quadratic dependence on the strong convex...
Deanna Needell, Nathan Srebro, Rachel Ward
MP
2016
10 years 3 months ago
Error bounds for mixed integer linear optimization problems
We introduce computable a-priori and a-posteriori error bounds for optimality and feasibility of a point generated as the rounding of an optimal point of the LP relaxation of a mi...
Oliver Stein
MP
2016
10 years 3 months ago
Solving variational inequalities with monotone operators on domains given by Linear Minimization Oracles
The standard algorithms for solving large-scale convex-concave saddle point problems, or, more generally, variational inequalities with monotone operators, are proximal type algor...
Anatoli Juditsky, Arkadi Nemirovski
MP
2016
10 years 3 months ago
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
We introduce a proximal version of the stochastic dual coordinate ascent method and show how to accelerate the method using an inner-outer iteration procedure. We analyze the runt...
Shai Shalev-Shwartz, Tong Zhang 0001
MP
2016
10 years 3 months ago
Accelerated gradient methods for nonconvex nonlinear and stochastic programming
In this paper, we generalize the well-known Nesterov’s accelerated gradient (AG) method, originally designed for convex smooth optimization, to solve nonconvex and possibly stoch...
Saeed Ghadimi, Guanghui Lan
MP
2016
10 years 3 months ago
A deterministic rescaled perceptron algorithm
The perceptron algorithm is a simple iterative procedure for finding a point in a convex cone F. At each iteration, the algorithm only involves a query to a separation oracle for...
Javier Peña, Negar Soheili
MP
2016
10 years 3 months ago
A dynamic inequality generation scheme for polynomial programming
Abstract Hierarchies of semidefinite programs have been used to approximate or even solve polynomial programs. This approach rapidly becomes computationally expensive and is often...
Bissan Ghaddar, Juan C. Vera, Miguel F. Anjos
MP
2016
10 years 3 months ago
Ray projection for optimizing polytopes with prohibitively many constraints in set-covering column generation
A recurrent task in mathematical programming requires optimizing polytopes with prohibitivelymany constraints, e.g., the primal polytope in cutting-plane methods or the dual polyt...
Daniel Porumbel