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KAIS
2008
221views more  KAIS 2008»
13 years 5 months ago
Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
Kun Zhang, Wei Fan
JCB
2007
198views more  JCB 2007»
13 years 5 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
ECCV
2006
Springer
14 years 7 months ago
Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
David J. Crandall, Daniel P. Huttenlocher
MM
2009
ACM
252views Multimedia» more  MM 2009»
13 years 12 months ago
Localizing volumetric motion for action recognition in realistic videos
This paper presents a novel motion localization approach for recognizing actions and events in real videos. Examples include StandUp and Kiss in Hollywood movies. The challenge ca...
Xiao Wu, Chong-Wah Ngo, Jintao Li, Yongdong Zhang
BMCBI
2006
165views more  BMCBI 2006»
13 years 5 months ago
Improved variance estimation of classification performance via reduction of bias caused by small sample size
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Ulrika Wickenberg-Bolin, Hanna Göransson, M&a...