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ICML
2004
IEEE
14 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
AUTOMATICA
2006
150views more  AUTOMATICA 2006»
13 years 7 months ago
Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
Chong Jin Ong, Dan Sui, Elmer G. Gilbert
ICTAI
2010
IEEE
13 years 5 months ago
Support Vector Methods for Sentence Level Machine Translation Evaluation
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as B...
Antoine Veillard, Elvina Melissa, Cassandra Theodo...
SEAL
2010
Springer
13 years 6 months ago
Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods
In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs....
Karel Crombecq, Tom Dhaene
ECML
1998
Springer
13 years 12 months ago
Learning to Classify X-Ray Images Using Relational Learning
: Image understanding often requires extensive background knowledge. The problem addressed in this paper is such knowledge can be acquired. We discuss how relational machine learni...
Claude Sammut, Tatjana Zrimec