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» Learning SVMs from Sloppily Labeled Data
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CVPR
2008
IEEE
14 years 10 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
NIPS
2003
13 years 9 months ago
Learning with Local and Global Consistency
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal,...
ICMCS
2006
IEEE
125views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Label Disambiguation and Sequence Modeling for Identifying Human Activities from Wearable Physiological Sensors
Wearable physiological sensors can provide a faithful record of a patient’s physiological states without constant attention of caregivers. A computer program that can infer huma...
Wei-Hao Lin, Alexander G. Hauptmann
NIPS
2003
13 years 9 months ago
Log-Linear Models for Label Ranking
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
Ofer Dekel, Christopher D. Manning, Yoram Singer
SIGIR
2008
ACM
13 years 7 months ago
Learning query intent from regularized click graphs
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
Xiao Li, Ye-Yi Wang, Alex Acero