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SIAMJO
2010
89views more  SIAMJO 2010»
12 years 11 months ago
A New Sequential Optimality Condition for Constrained Optimization and Algorithmic Consequences
Necessary first-order sequential optimality conditions provide adequate theoretical tools to justify stopping criteria for nonlinear programming solvers. These conditions are sati...
Roberto Andreani, José Mario Martíne...
ICASSP
2008
IEEE
13 years 11 months ago
A new Particle Filtering algorithm with structurally optimal importance function
Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
Boujemaa Ait-El-Fquih, François Desbouvries
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
14 years 5 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
EVOW
2007
Springer
13 years 11 months ago
Combining Lagrangian Decomposition with an Evolutionary Algorithm for the Knapsack Constrained Maximum Spanning Tree Problem
We present a Lagrangian decomposition approach for the Knapsack Constrained Maximum Spanning Tree problem yielding upper bounds as well as heuristic solutions. This method is furth...
Sandro Pirkwieser, Günther R. Raidl, Jakob Pu...
SIAMJO
2010
83views more  SIAMJO 2010»
13 years 3 months ago
The Lifted Newton Method and Its Application in Optimization
Abstract. We present a new “lifting” approach for the solution of nonlinear optimization problems (NLPs) that have objective and constraint functions with intermediate variable...
Jan Albersmeyer, Moritz Diehl