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» Sampling Bounds for Stochastic Optimization
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ECCV
2006
Springer
14 years 11 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
Charles Florin, Nikos Paragios, James Williams
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
14 years 2 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
CORR
2010
Springer
134views Education» more  CORR 2010»
13 years 10 months ago
Incremental Sampling-based Algorithms for Optimal Motion Planning
During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to po...
Sertac Karaman, Emilio Frazzoli
PAKDD
2007
ACM
115views Data Mining» more  PAKDD 2007»
14 years 4 months ago
Intelligent Sequential Mining Via Alignment: Optimization Techniques for Very Large DB
The shear volume of the results in traditional support based frequent sequential pattern mining methods has led to increasing interest in new intelligent mining methods to find mo...
Hye-Chung Kum, Joong Hyuk Chang, Wei Wang 0010
IPCO
2007
108views Optimization» more  IPCO 2007»
13 years 11 months ago
Robust Combinatorial Optimization with Exponential Scenarios
Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...
Uriel Feige, Kamal Jain, Mohammad Mahdian, Vahab S...