| % | |
Name |
Content type |
|---|
|
100%
|
|
Machine Learning for Optimisation and Services
Machine Learning for Optimisation and Services ...
The MLS area at XRCE (Machine Learning for Optimisation and Services) addresses issues raised to two wide areas of research: machine learning and process control.
See an example
The main ...
Research group that concentrates on learning from data to provide optimal decision making
|
Page |
|
89%
|
|
Machine Learning for Optimisation and Services : Example
Machine Learning for Optimisation and Services : Example
|
Page |
|
68%
|
|
Simon Lacoste-Julien - Discriminative Machine Learning with Structure
Discriminative Machine Learning with Structure ...
Real world problems such as machine translation involve complex dependencies. Generative models formulate it as a weighted bipartite matching problem and show how to learn the weights by using a large
|
Seminar |
|
61%
|
|
2001/012 - Wrapping Web Information Providers by Transducer Induction
iwrap, machine learning ... European Conference on Machine Learning, Freiburg, Germany, September 3-7, 2001 ... and to annotate it with
user-defined labels. A number of approaches exploit the methods of machine learning
|
Publication |
|
59%
|
|
1999/307 - Unsupervised Learning of Derivational Morphology from Inflectional Lexicons
Unsupervised Learning of Derivational Morphology from Inflectional Lexicons ... Machine Learning, derivational morphology
|
Publication |
|
54%
|
|
2002/010 - Word-Sequence Kernels
Kernel machines text categorisation linguistic processing string kernels ... The Journal of Machine Learning Research ...
machines. Since the work of Joachims (1998), there is ample experimental evidence that SVM using
|
Publication |
|
53%
|
|
2005/050 - Traitement automatique pour la Migration de Documents Numériques vers XML
machine learning, information extraction, xml ... module uses supervised machine learning technique to learn a conversion model for a collection
|
Publication |
|
52%
|
|
2006/031 - Reducing the annotation burden in text classification
semi-supervised learning, active learning, PLSA, Machine Learning ... In this paper we describe a method which combines semi-supervised and active learning ) algorithm [4] combined with a certainty-based active learning method, in order to classify text documents.
|
Publication |
|
51%
|
|
2008/020 - A Statistical Machine Translation Primer
A Statistical Machine Translation Primer ... Introduction to the Volume « Learning Machine Translation », ... in the future. We put this in the general context of Machine Learning research, and put the emphasis on similarities and differences with standard Machine Learning problems and practice.
|
Publication |
|
51%
|
|
2009/037 - Machine Learning Classification for Document Review
Machine Learning Classification for Document Review ... of documents most likely to be responsive. Further, machine learning textual classification can augment corporate budgets. One of these new approaches is the subject of this paper. Specifically, applying machine
|
Publication |
