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CVPR
2008
IEEE
16 years 8 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
199
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MICAI
2007
Springer
16 years 27 days ago
An EM Algorithm to Learn Sequences in the Wavelet Domain
The wavelet transform has been used for feature extraction in many applications of pattern recognition. However, in general the learning algorithms are not designed taking into acc...
Diego H. Milone, Leandro E. Di Persia
CVPR
2011
IEEE
15 years 2 months ago
Learning Message-Passing Inference Machines for Structured Prediction
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Stephane Ross, Daniel Munoz, J. Andrew Bagnell
ACL
2012
13 years 9 months ago
Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
This paper uses an unsupervised model of grounded language acquisition to study the role that social cues play in language acquisition. The input to the model consists of (orthogr...
Mark Johnson, Katherine Demuth, Michael C. Frank
AAMAS
2005
Springer
15 years 6 months ago
Learning and Exploiting Relative Weaknesses of Opponent Agents
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Shaul Markovitch, Ronit Reger