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ECAL
2005
Springer
14 years 1 months ago
A Self-organising, Self-adaptable Cellular System
Abstract. Inspired by the recent advances in evolutionary biology, we have developed a self-organising, self-adaptable cellular system for multitask learning. The main aim of our p...
Lucien Epiney, Mariusz Nowostawski
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
ACTAC
2006
126views more  ACTAC 2006»
13 years 7 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
KES
2004
Springer
14 years 29 days ago
Epistemic Logic and Planning
Artificial Intelligence algorithms can be divided into two groups according to the type of problems they solve. Knowledge-intensive domains contain explicit knowledge, whereas know...
Shahin Maghsoudi, Ian Watson