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ICCV
2007
IEEE
14 years 10 months ago
Learning Structured Appearance Models from Captioned Images of Cluttered Scenes
Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to learn both the names and appearances of the objects. Only a...
Michael Jamieson, Afsaneh Fazly, Sven J. Dickinson...
CVPR
2008
IEEE
13 years 10 months ago
Loose shape model for discriminative learning of object categories
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
Margarita Osadchy, Elran Morash
NIPS
2003
13 years 10 months ago
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
Marc Toussaint
ACL
2008
13 years 10 months ago
Analyzing the Errors of Unsupervised Learning
We identify four types of errors that unsupervised induction systems make and study each one in turn. Our contributions include (1) using a meta-model to analyze the incorrect bia...
Percy Liang, Dan Klein
ICCV
2003
IEEE
14 years 10 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...