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CVPR
1999
IEEE
14 years 9 months ago
Shape from Recognition and Learning: Recovery of 3-D Face Shapes
In this paper, a novel framework for the recovery of 3D surfaces of faces from single images is developed. The underlying principle is shape from recognition, i.e. the idea that p...
Dibyendu Nandy, Jezekiel Ben-Arie
SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
13 years 9 months ago
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
PAMI
2006
206views more  PAMI 2006»
13 years 7 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
COLT
2005
Springer
14 years 1 months ago
A PAC-Style Model for Learning from Labeled and Unlabeled Data
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
Maria-Florina Balcan, Avrim Blum
CVPR
2010
IEEE
13 years 8 months ago
Total Bregman divergence and its applications to shape retrieval
Shape database search is ubiquitous in the world of biometric systems, CAD systems etc. Shape data in these domains is experiencing an explosive growth and usually requires search...
Meizhu Liu, Baba C. Vemuri, Shun-ichi Amari, Frank...