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ML
2007
ACM
130views Machine Learning» more  ML 2007»
15 years 4 months ago
Interactive learning of node selecting tree transducer
We develop new algorithms for learning monadic node selection queries in unranked trees from annotated examples, and apply them to visually interactive Web information extraction. ...
Julien Carme, Rémi Gilleron, Aurélie...
SAC
2010
ACM
14 years 11 months ago
A new methodology for photometric validation in vehicles visual interactive systems
This work proposes a new methodology for automatically validating the internal lighting system of an automotive, i.e., assessing the visual quality of an instrument cluster (IC) f...
Alexandre W. C. Faria, David Menotti, Daniel S. D....
BMCBI
2011
14 years 8 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
16 years 5 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
GECCO
2009
Springer
141views Optimization» more  GECCO 2009»
15 years 11 months ago
Distributed hyper-heuristics for real parameter optimization
Hyper-heuristics (HHs) are heuristics that work with an arbitrary set of search operators or algorithms and combine these algorithms adaptively to achieve a better performance tha...
Marco Biazzini, Balázs Bánhelyi, Alb...