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» Evaluating algorithms that learn from data streams
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SIGIR
2006
ACM
15 years 10 months ago
Learning a ranking from pairwise preferences
We introduce a novel approach to combining rankings from multiple retrieval systems. We use a logistic regression model or an SVM to learn a ranking from pairwise document prefere...
Ben Carterette, Desislava Petkova
MCAM
2007
Springer
127views Multimedia» more  MCAM 2007»
15 years 10 months ago
An Optimized Topology Maintenance Framework for P2P Media Streaming
In this paper, we present an optimized topology maintenance framework used in AVStreamer P2P media streaming system. To help new incoming clients get an initial view of the whole n...
Rui Guo, Longshe Huo, Qiang Fu, Shuangjia Chen, We...
ICML
2006
IEEE
16 years 5 months ago
Learning user preferences for sets of objects
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Marie desJardins, Eric Eaton, Kiri Wagstaff
IPSN
2003
Springer
15 years 9 months ago
Hypothesis Testing over Factorizations for Data Association
Abstract. The issue of data association arises frequently in sensor networks; whenever multiple sensors and sources are present, it may be necessary to determine which observations...
Alexander T. Ihler, John W. Fisher III, Alan S. Wi...
GIS
2008
ACM
16 years 5 months ago
Sharing and exploring sensor streams over geocentric interfaces
We present SenseWeb, an open and scalable infrastructure for sharing and geocentric exploration of sensor data streams. SenseWeb allows sensor owners to share data streams across ...
Liqian Luo, Aman Kansal, Suman Nath, Feng Zhao