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» Learning Functions from Imperfect Positive Data
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104
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CIDM
2007
IEEE
15 years 6 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
125
Voted
IJAR
2007
130views more  IJAR 2007»
15 years 2 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
128
Voted
WSDM
2012
ACM
214views Data Mining» more  WSDM 2012»
13 years 10 months ago
Selecting actions for resource-bounded information extraction using reinforcement learning
Given a database with missing or uncertain content, our goal is to correct and fill the database by extracting specific information from a large corpus such as the Web, and to d...
Pallika H. Kanani, Andrew K. McCallum
133
Voted
ICPR
2010
IEEE
15 years 7 months ago
Active Boosting for Interactive Object Retrieval
This paper presents a new algorithm based on boosting for interactive object retrieval in images. Recent works propose ”online boosting” algorithms where weak classifier sets...
Alexis Lechervy, Philippe Henri Gosselin, Frederic...
137
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HUMO
2000
Springer
15 years 6 months ago
A Computational Model for Motion Detection and Direction Discrimination in Humans
Seeing biological motion is very important for both humans and computers. Psychophysics experiments show that the ability of our visual system for biological motion detection and ...
Yang Song, Pietro Perona