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» A Framework for Multiple-Instance Learning
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ICCV
2009
IEEE
15 years 2 months ago
Learning Pedestrian Dynamics from the Real World
In this paper we describe a method to learn parameters which govern pedestrian motion by observing video data. Our learning framework is based on variational mode learning and a...
Paul Scovanner, Marshall Tappen
ICCBR
2005
Springer
14 years 2 months ago
Learning Semantic Annotations for Textual Cases
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
Eni Mustafaraj, Martin Hoof, Bernd Freisleben
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
14 years 3 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...
SIGCSE
2004
ACM
110views Education» more  SIGCSE 2004»
14 years 2 months ago
An extensible framework for providing dynamic data structure visualizations in a lightweight IDE
A framework for producing dynamic data structure visualizations within the context of a lightweight IDE is described. Multiple synchronized visualizations of a data structure can ...
T. Dean Hendrix, James H. Cross II, Larry A. Barow...
AINA
2006
IEEE
14 years 28 days ago
Constrained Flooding: A Robust and Efficient Routing Framework for Wireless Sensor Networks
Flooding protocols for wireless networks in general have been shown to be very inefficient and therefore are mainly used in network initialization or route discovery and maintenan...
Ying Zhang, Markus P. J. Fromherz