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EMMCVPR
2005
Springer
15 years 11 months ago
Learning Hierarchical Shape Models from Examples
Abstract. We present an algorithm for automatically constructing a decompositional shape model from examples. Unlike current approaches to structural model acquisition, in which on...
Alex Levinshtein, Cristian Sminchisescu, Sven J. D...
FLAIRS
2003
15 years 6 months ago
Orthographic Case Restoration Using Supervised Learning Without Manual Annotation
One challenge in text processing is the treatment of case insensitive documents such as speech recognition results. The traditional approach is to re-train a language model exclud...
Cheng Niu, Wei Li 0003, Jihong Ding, Rohini K. Sri...
183
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METMBS
2003
255views Mathematics» more  METMBS 2003»
15 years 6 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
WWW
2010
ACM
16 years 15 days ago
Find me if you can: improving geographical prediction with social and spatial proximity
Geography and social relationships are inextricably intertwined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data re...
Lars Backstrom, Eric Sun, Cameron Marlow
IJCAI
1989
15 years 6 months ago
Coping With Uncertainty in Map Learning
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
Kenneth Basye, Thomas Dean, Jeffrey Scott Vitter