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» Variational methods for Reinforcement Learning
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CVPR
2006
IEEE
14 years 1 months ago
Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Xiaoyang Tan, Songcan Chen, Jun Li, Zhi-Hua Zhou
NIPS
2004
13 years 9 months ago
Incremental Learning for Visual Tracking
Most existing tracking algorithms construct a representation of a target object prior to the tracking task starts, and utilize invariant features to handle appearance variation of...
Jongwoo Lim, David A. Ross, Ruei-Sung Lin, Ming-Hs...
AAAI
2011
12 years 7 months ago
Using Semantic Cues to Learn Syntax
We present a method for dependency grammar induction that utilizes sparse annotations of semantic relations. This induction set-up is attractive because such annotations provide u...
Tahira Naseem, Regina Barzilay
ICML
2006
IEEE
14 years 8 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
SI3D
2010
ACM
14 years 2 months ago
Learning skeletons for shape and pose
In this paper a method for estimating a rigid skeleton, including skinning weights, skeleton connectivity, and joint positions, given a sparse set of example poses is presented. I...
Nils Hasler, Thorsten Thormählen, Bodo Rosenh...