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» Learning Models for Object Recognition
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ICML
2009
IEEE
16 years 2 months ago
Uncertainty sampling and transductive experimental design for active dual supervision
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...
110
Voted
ICML
2007
IEEE
16 years 2 months ago
Statistical predicate invention
We propose statistical predicate invention as a key problem for statistical relational learning. SPI is the problem of discovering new concepts, properties and relations in struct...
Stanley Kok, Pedro Domingos
108
Voted
ICML
2004
IEEE
16 years 2 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
ECCV
2004
Springer
16 years 3 months ago
A Visual Category Filter for Google Images
We extend the constellation model to include heterogeneous parts which may represent either the appearance or the geometry of a region of the object. The parts and their spatial co...
Robert Fergus, Pietro Perona, Andrew Zisserman
135
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AVSS
2006
IEEE
15 years 7 months ago
Recognizing Facial Expressions in Videos Using a Facial Action Analysis-Synthesis Scheme
In this paper, we propose a novel approach for facial expression analysis and recognition. The proposed approach relies on tracked facial actions provided by an appearance-based 3...
Fadi Dornaika, Bogdan Raducanu