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COLING
1996
15 years 4 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel
129
Voted
CVPR
2009
IEEE
16 years 10 months ago
Discriminative Structure Learning of Hierarchical Representations for Object Detection
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
ICML
2009
IEEE
16 years 4 months ago
Structure learning with independent non-identically distributed data
There are well known algorithms for learning the structure of directed and undirected graphical models from data, but nearly all assume that the data consists of a single i.i.d. s...
Robert E. Tillman
ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 3 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
ACCV
2010
Springer
14 years 10 months ago
Learning Image Structures for Optimizing Disparity Estimation
We present a method for optimizing the stereo matching process when it is applied to a series of images with similar depth structures. We observe that there are similar regions wit...
M. V. Rohith, Chandra Kambhamettu