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INFFUS
2008
97views more  INFFUS 2008»
15 years 4 months ago
Using classifier ensembles to label spatially disjoint data
act 11 We describe an ensemble approach to learning from arbitrarily partitioned data. The partitioning comes from the distributed process12 ing requirements of a large scale simul...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
161
Voted
CA
1999
IEEE
15 years 9 months ago
Fast Synthetic Vision, Memory, and Learning Models for Virtual Humans
This paper presents a simple and efficient method of modeling synthetic vision, memory, and learning for autonomous animated characters in real-time virtual environments. The mode...
James J. Kuffner Jr., Jean-Claude Latombe
VLDB
1998
ACM
147views Database» more  VLDB 1998»
15 years 9 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
APWEB
2003
Springer
15 years 8 months ago
Mining "Hidden Phrase" Definitions from the Web
Keyword searching is the most common form of document search on the Web. Many Web publishers manually annotate the META tags and titles of their pages with frequently queried phras...
Hung V. Nguyen, P. Velamuru, Deepak Kolippakkam, H...
ALT
2005
Springer
16 years 1 months ago
Non U-Shaped Vacillatory and Team Learning
U-shaped learning behaviour in cognitive development involves learning, unlearning and relearning. It occurs, for example, in learning irregular verbs. The prior cognitive science...
Lorenzo Carlucci, John Case, Sanjay Jain, Frank St...