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» Analysis of Perceptron-Based Active Learning
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ICML
2010
IEEE
13 years 8 months ago
Active Learning for Networked Data
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor
TMI
2002
259views more  TMI 2002»
13 years 7 months ago
3-D Active Appearance Models: Segmentation of Cardiac MR and Ultrasound Images
A model-based method for three-dimensional image segmentation was developed and its performance assessed in segmentation of volumetric cardiac magnetic resonance (MR) images and ec...
Steven C. Mitchell, Johan G. Bosch, Boudewijn P. F...
ICML
2006
IEEE
14 years 8 months ago
Active learning via transductive experimental design
This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple conc...
Kai Yu, Jinbo Bi, Volker Tresp
COLT
2010
Springer
13 years 5 months ago
Robust Selective Sampling from Single and Multiple Teachers
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
Ofer Dekel, Claudio Gentile, Karthik Sridharan
ICC
2007
IEEE
217views Communications» more  ICC 2007»
14 years 1 months ago
Decentralized Activation in a ZigBee-enabled Unattended Ground Sensor Network: A Correlated Equilibrium Game Theoretic Analysis
Abstract— We describe a decentralized learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. Sensor nodes learn to monitor their environment i...
Michael Maskery, Vikram Krishnamurthy