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» SUSTAIN: A Model of Human Category Learning
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CVPR
2010
IEEE
16 years 1 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...
WWW
2006
ACM
16 years 6 months ago
Large-scale text categorization by batch mode active learning
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
JFR
2006
88views more  JFR 2006»
15 years 6 months ago
Discovering natural kinds of robot sensory experiences in unstructured environments
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...
WWW
2004
ACM
16 years 6 months ago
KnowledgeTree: a distributed architecture for adaptive e-learning
This paper presents KnowledgeTree, an architecture for adaptive E-Learning based on distributed reusable intelligent learning activities. The goal of KnowledgeTree is to bridge th...
Peter Brusilovsky
ICMI
2004
Springer
183views Biometrics» more  ICMI 2004»
15 years 11 months ago
Agent and library augmented shared knowledge areas (ALASKA)
This paper reports on an NSF-funded effort now underway to integrate three learning technologies that have emerged and matured over the past decade; each has presented compelling ...
Eric R. Hamilton