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Learning paradigms involving varying levels of supervision have received a lot of interest within the computer vision and machine learning communities.
Combining labeled and unlabeled data with co-training
A. Blum and T. Mitchell · 1998
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Coactive Learning for Distributed Data Mining
D. L. Grecu and L. A. Becker · 1998
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Collaborative learning for recommender systems
W. S. Lee · 2001
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Unsupervised improvement of visual detectors using co-training
A. Levin, P. Viola, and Y. Freund · 2003
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Collaborative filtering: A machine learning perspective
B. Marlin · 2004
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Learning a similarity metric discriminatively, with application to face verification
S. Chopra, R. Hadsell, and Y. LeCun · 2005
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Semi-supervised learning literature survey
X. Zhu · 2005
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Co-adaptation of audio-visual speech and gesture classifiers
C. M. Christoudias, K. Saenko, L.-P. Morency, and T. Darrell · 2006
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Minimising semantic drift with mutual exclusion bootstrapping
J. R. Curran, T. Murphy, and B. Scholz · 2007
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Human-robot interaction: A survey
M. A. Goodrich and A. C. Schultz · 2007
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Multi-task learning for classification with dirichlet process priors
Y. Xue, X. Liao, L. Carin, and B. Krishnapuram · 2007
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FaceTracer: A Search Engine for Large Collections of Images with Faces
N. Kumar, P. N. Belhumeur, and S. K. Nayar · 2008
Earlier work this paper cites.
Describing objects by their attributes
A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth · 2009
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Attribute and simile classifiers for face verification
N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar · 2009
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Learning to detect unseen object classes by betweenclass attribute transfer
C. H. Lampert, H. Nickisch, and S. Harmeling · 2009
Cited alongside, same era.
Adapting visual category models to new domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
Cited alongside, same era.
Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms
L. Bo, X. Ren, and D. Fox · 2011
Cited alongside, same era.
A large-scale hierarchical multi-view rgb-d object dataset
K. Lai, L. Bo, X. Ren, and D. Fox · 2011
Cited alongside, same era.
Unsupervised Feature Learning for RGB-D Based Object Recognition
L. Bo, X. Ren, and D. Fox · 2012
Cited alongside, same era.
Discovering latent domains for multisource domain adaptation
J. Hoffman, B. Kulis, T. Darrell, and K. Saenko · 2012
Cited alongside, same era.
Multipath sparse coding using hierarchical matching pursuit
L. Bo, X. Ren, and D. Fox · 2013
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Semi-supervised domain adaptation with instance constraints
J. Donahue, J. Hoffman, E. Rodner, K. Saenko, and T. Darrell · 2013
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Efficient learning of domain-invariant image representations
J. Hoffman, E. Rodner, J. Donahue, K. Saenko, and T. Darrell · 2013
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Attribute Based Object Identification
Y. Sun, L. Bo, and D. Fox · 2013
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HOGgles: Visualizing Object Detection Features
C. Vondrick, A. Khosla, T. Malisiewicz, and A. Torralba · 2013
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Interactively Guiding Semi-Supervised Clustering via Attribute-based Explanations
S. Lad and D. Parikh · 2014
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Whittlesearch: Image search with relative attribute feedback
D. Parikh, A. Kovashka, and K. Grauman · 2012
Cited alongside, same era.
Attributes for classifier feedback
A. Parkash and D. Parikh · 2012
Cited alongside, same era.
Sun attribute database: Discovering, annotating, and recognizing scene attributes
G. Patterson and J. Hays · 2012
Cited alongside, same era.
Exploiting unrelated tasks in multi-task learning
B. Romera-Paredes, A. Argyriou, N. Berthouze, and M. Pontil · 2012
Cited alongside, same era.
Online structured prediction via coactive learning
P. Shivaswamy and T. Joachims · 2012
Cited alongside, same era.
Constrained semi-supervised learning using attributes and comparative attributes
A. Shrivastava, S. Singh, and A. Gupta · 2012
Cited alongside, same era.
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Understanding deep image representations by inverting them
A. Mahendran and A. Vedaldi · 2014
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Dense semantic image segmentation with objects and attributes
S. Zheng, M.-M. Cheng, J. Warrell, P. Sturgess, V. Vineet, C. Rother, and P. H. Torr · 2014
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Learning to compare image patches via convolutional neural networks
S. Zagoruyko and N. Komodakis · 2015
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Cross-modal scene networks
Y. Aytar, L. Castrejon, C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
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Learning aligned cross-modal representations from weakly aligned data
L. Castrejon, Y. Aytar, C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
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Cross modal distillation for supervision transfer
S. Gupta, J. Hoffman, and J. Malik · 2016
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Learning with side information through modality hallucination
J. Hoffman, S. Gupta, and T. Darrell · 2016
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