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» Learning Models for Predicting Recognition Performance
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126
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STOC
2005
ACM
129views Algorithms» more  STOC 2005»
16 years 2 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
ICCV
2011
IEEE
14 years 2 months ago
Learning Universal Multi-view Age Estimator by Video Contexts
Most existing techniques for analyzing face images assume that the faces are at near-frontal poses. Generalizing to non-frontal faces is often difficult, due to a dearth of groun...
Zheng Song, Bingbing Ni, Dong Guo, Terence Sim, Sh...
141
Voted
ICCV
2005
IEEE
16 years 4 months ago
Building a Classification Cascade for Visual Identification from One Example
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
139
Voted
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
15 years 4 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...
139
Voted
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
15 years 14 days ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim