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» Learning to learn with the informative vector machine
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MLMI
2005
Springer
14 years 2 months ago
Foreground Regions Extraction and Characterization Towards Real-Time Object Tracking
Abstract. Object localization and tracking are key issues in the analysis of scenes for video surveillance or scene understanding applications. This paper presents a contribution t...
José Luis Landabaso, Montse Pardàs
FTML
2008
185views more  FTML 2008»
13 years 9 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
ICDM
2009
IEEE
107views Data Mining» more  ICDM 2009»
13 years 6 months ago
Naive Bayes Classification of Uncertain Data
Traditional machine learning algorithms assume that data are exact or precise. However, this assumption may not hold in some situations because of data uncertainty arising from mea...
Jiangtao Ren, Sau Dan Lee, Xianlu Chen, Ben Kao, R...
CROSSROADS
2010
13 years 4 months ago
Massive multiplayer human computation for fun, money, and survival
Crowdsourcing is an effective tool to solve hard tasks. By bringing 100,000s of people to work on simple tasks that only humans can do, we can go far beyond traditional models of ...
Lukas Biewald
ICDAR
2011
IEEE
12 years 8 months ago
Functional-Based Table Category Identification in Digital Library
– Better understanding the document logical components is crucial to many applications, e.g., document classification or data integration. As the development of digital libraries...
Seongchan Kim, Ying Liu