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» Structured Learning with Approximate Inference
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CVPR
2008
IEEE
15 years 11 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
ECAGENTS
2001
Springer
127views ECommerce» more  ECAGENTS 2001»
15 years 2 months ago
User-Centered Agents for Structured Information Location
Abstract. This paper designs an electronic commerce system that integrates conventional electronic commerce services with contemporary WWW advantages, such as comprehensive coverag...
Xindong Wu, Daniel Ngu, Sameer Pradhan
ACMICEC
2007
ACM
102views ECommerce» more  ACMICEC 2007»
15 years 1 months ago
Learning to trade with insider information
This paper introduces algorithms for learning how to trade using insider (superior) information in Kyle's model of financial markets. Prior results in finance theory relied o...
Sanmay Das
ICML
2009
IEEE
15 years 10 months ago
Nonparametric factor analysis with beta process priors
We propose a nonparametric extension to the factor analysis problem using a beta process prior. This beta process factor analysis (BPFA) model allows for a dataset to be decompose...
John William Paisley, Lawrence Carin
ESWS
2009
Springer
15 years 4 months ago
Ranking Approximate Answers to Semantic Web Queries
We consider the problem of a user querying semistructured data such as RDF without knowing its structure. In these circumstances, it is helpful if the querying system can perform a...
Carlos A. Hurtado, Alexandra Poulovassilis, Peter ...