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» An Introduction to Transfer Learning
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LCN
1998
IEEE
14 years 2 months ago
Multicasting Multimedia Streams with Active Networks
Active networks allow code to be loaded dynamically into network nodes at run-time. This code can perform tasks specific to a stream of packets or even a single packet. In this pa...
Albert Banchs, Wolfgang Effelsberg, Christian F. T...
TVCG
2010
183views more  TVCG 2010»
13 years 8 months ago
Exploration and Visualization of Segmentation Uncertainty using Shape and Appearance Prior Information
—We develop an interactive analysis and visualization tool for probabilistic segmentation in medical imaging. The originality of our approach is that the data exploration is guid...
Ahmed Saad, Ghassan Hamarneh, Torsten Möller
AAAI
2012
12 years 9 days ago
Transportability of Causal Effects: Completeness Results
The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...
Elias Bareinboim, Judea Pearl
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
14 years 3 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
KDD
2010
ACM
286views Data Mining» more  KDD 2010»
13 years 8 months ago
Nonnegative shared subspace learning and its application to social media retrieval
Although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. These factors can ser...
Sunil Kumar Gupta, Dinh Q. Phung, Brett Adams, Tru...