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TIT
2008
61views more  TIT 2008»
15 years 2 months ago
A Probabilistic Upper Bound on Differential Entropy
A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution...
Erik G. Learned-Miller, Joseph DeStefano
ECCV
2008
Springer
16 years 4 months ago
Discriminative Learning for Deformable Shape Segmentation: A Comparative Study
Abstract. We present a comparative study on how to use discriminative learning methods such as classification, regression, and ranking to address deformable shape segmentation. Tra...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
CVPR
2001
IEEE
16 years 5 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
CVPR
2010
IEEE
15 years 10 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
ICRA
2003
IEEE
222views Robotics» more  ICRA 2003»
15 years 8 months ago
Path planning using learned constraints and preferences
— In this paper we present a novel method for robot path planning based on learning motion patterns. A motion pattern is defined as the path that results from applying a set of ...
Gregory Dudek, Saul Simhon