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CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 9 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
FGR
2006
IEEE
297views Biometrics» more  FGR 2006»
14 years 2 months ago
Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning
Skin segmentation is the cornerstone of many applications such as gesture recognition, face detection, and objectionable image filtering. In this paper, we attempt to address the ...
Junwei Han, George Awad, Alistair Sutherland, Hai ...
MICAI
2004
Springer
14 years 2 months ago
An Optimization Algorithm Based on Active and Instance-Based Learning
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
Olac Fuentes, Thamar Solorio
MM
2005
ACM
160views Multimedia» more  MM 2005»
14 years 2 months ago
Putting active learning into multimedia applications: dynamic definition and refinement of concept classifiers
The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays...
Ming-yu Chen, Michael G. Christel, Alexander G. Ha...
IJCAI
2003
13 years 10 months ago
Active Learning with Strong and Weak Views: A Case Study on Wrapper Induction
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
Ion Muslea, Steven Minton, Craig A. Knoblock