2031 search results - page 86 / 407 » Approximation Algorithms for 2-Stage Stochastic Optimization... |
ACL
2009
13 years 6 months ago
2009
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
SODA
2010
ACM
14 years 5 months ago
2010
ACM
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
GECCO
2004
Springer
14 years 1 months ago
2004
Springer
Several inverse problems exist in the atmospheric sciences that are computationally costly when using traditional gradient based methods. Unfortunately, many standard evolutionary ...
ESA
2001
Springer
14 years 18 days ago
2001
Springer
In this paper we introduce a general strategy for approximating the solution to minimisation problems in random regular graphs. We describe how the approach can be applied to the m...
CORR
2011
Springer
13 years 2 months ago
2011
Springer
We analyze a class of estimators based on a convex relaxation for solving highdimensional matrix decomposition problems. The observations are the noisy realizations of the sum of ...