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KDD
2010
ACM
247views Data Mining» more  KDD 2010»
15 years 6 months ago
Active learning for biomedical citation screening
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
CVPR
2008
IEEE
16 years 6 months ago
Unsupervised modeling of object categories using link analysis techniques
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
Gunhee Kim, Christos Faloutsos, Martial Hebert
CHI
2004
ACM
16 years 5 months ago
Science at the Speed of Thought
Abstract. In this paper we describe a virtual laboratory that is designed to accelerate scientific exploration and discovery by minimizing the time between the generation of a scie...
Judith Ellen Devaney, Steven G. Satterfield, John ...
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 10 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
COLT
2001
Springer
15 years 9 months ago
Geometric Bounds for Generalization in Boosting
We consider geometric conditions on a labeled data set which guarantee that boosting algorithms work well when linear classifiers are used as weak learners. We start by providing ...
Shie Mannor, Ron Meir