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» On learning algorithm selection for classification
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EMNLP
2008
15 years 8 months ago
Online Methods for Multi-Domain Learning and Adaptation
NLP tasks are often domain specific, yet systems can learn behaviors across multiple domains. We develop a new multi-domain online learning framework based on parameter combinatio...
Mark Dredze, Koby Crammer
PAMI
2008
175views more  PAMI 2008»
15 years 6 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
ATAL
2011
Springer
14 years 6 months ago
Forgetting through generalisation: a companion with selective memory
This research investigates event generalisation in computational episodic memory for artificial companions. Two studies indicated a preference of a biologically-inspired selectiv...
Mei Yii Lim, Ruth Aylett, Patrícia Amâ...
GPEM
2008
128views more  GPEM 2008»
15 years 6 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
IJCNN
2006
IEEE
16 years 20 days ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho