Sciweavers

451 search results - page 25 / 91
» Approximation algorithms for stochastic orienteering
Sort
View
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
14 years 2 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
ACL
2009
13 years 6 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
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...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
ICPR
2008
IEEE
14 years 10 months ago
Vector field resampling using local streamline approximation
In this paper, we propose an algorithm to resample coarse vector fields in order to obtain vector fields of a higher density. Unlike the typical linear interpolation scheme, our a...
Mani Thomas, Chandra Kambhamettu, Cathleen A. Geig...
UAI
2003
13 years 10 months ago
An Importance Sampling Algorithm Based on Evidence Pre-propagation
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
Changhe Yuan, Marek J. Druzdzel
JMLR
2010
129views more  JMLR 2010»
13 years 3 months ago
Approximation of hidden Markov models by mixtures of experts with application to particle filtering
Selecting conveniently the proposal kernel and the adjustment multiplier weights of the auxiliary particle filter may increase significantly the accuracy and computational efficie...
Jimmy Olsson, Jonas Ströjby