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ICCV
2005
IEEE
16 years 3 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICML
2009
IEEE
16 years 2 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
COLT
1992
Springer
15 years 5 months ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi
ATAL
2006
Springer
15 years 5 months ago
Multi-robot learning with particle swarm optimization
We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the lea...
Jim Pugh, Alcherio Martinoli
PERCOM
2008
ACM
15 years 1 months ago
An Infrastructure for Developing Pervasive Learning Environments
This paper presents an infrastructure for developing problem-based pervasive learning environments. Building such environments necessitates having many autonomous components deali...
Sabine Graf, Kathryn MacCallum, Tzu-Chien Liu, Mai...