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» Learning to Learn Causal Models
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CII
2008
100views more  CII 2008»
15 years 1 months ago
Knowledge formalization in experience feedback processes: An ontology-based approach
Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understa...
Bernard Kamsu Foguem, Thierry Coudert, C. Bé...
CORR
2010
Springer
149views Education» more  CORR 2010»
15 years 1 months ago
Using Rough Set and Support Vector Machine for Network Intrusion Detection
The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a ...
Rung Ching Chen, Kai-Fan Cheng, Chia-Fen Hsieh
CONSTRAINTS
2008
182views more  CONSTRAINTS 2008»
15 years 1 months ago
Constraint Programming in Structural Bioinformatics
Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry...
Pedro Barahona, Ludwig Krippahl
107
Voted
CORR
2010
Springer
167views Education» more  CORR 2010»
15 years 1 months ago
Network Flow Algorithms for Structured Sparsity
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...
CORR
2010
Springer
140views Education» more  CORR 2010»
15 years 1 months ago
Image Segmentation by Discounted Cumulative Ranking on Maximal Cliques
We propose a mid-level image segmentation framework that combines multiple figure-ground hypothesis (FG) constrained at different locations and scales, into interpretations that t...
João Carreira, Adrian Ion, Cristian Sminchi...
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