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Incorporating additional knowledge in the learning process can be beneficial for several computer vision and machine learning tasks.
Cross-domain video concept detection using adaptive SVMs
J. Yang, R. Yan, and A. Hauptmann · 2007
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Curriculum learning
Y. Bengio, J. Louradour, R. Collobert, and J. Weston · 2009
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A new learning paradigm: Learning using privileged information
V. Vapnik and A. Vashist · 2009
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Tabula rasa: Model transfer for object category detection
Y. Aytar and A. Zisserman · 2011
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Fast optimization algorithms for solving SVM+
D. Pechyony and V. Vapnik · 2011
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Deep learning of representations for unsupervised and transfer learning
Y. Bengio · 2012
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Domain adaptation from multiple sources: A domain-dependent regularization approach
L. Duan, D. Xu, and I. W.-H. Tsang · 2012
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Selective transfer machine for personalized facial action unit detection
W.-S. Chu, F. De la Torre, and J. F. Cohn · 2013
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Learning to rank using privileged information
V. Sharmanska, N. Quadrianto, and C. Lampert · 2013
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Zero-shot learning via visual abstraction
S. Antol, L. Zitnick, and D. Parikh · 2014
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Self-paced learning with diversity
L. Jiang, D. Meng, S. Yu, Z. Lan, S. Shan, and A. Hauptmann · 2014
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Attribute-based classification for zero-shot visual object categorization
C. Lampert, H. Nickisch, and S. Harmeling · 2014
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Learning using privileged information: SVM+ and weighted SVM
M. Lapin, M. Hein, and B. Schiele · 2014
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, L. Bourdev, R. Girshick, J. Hays, P. Perona, D. Ramanan, C. L. Zitnick, and P. Dollar · 2014
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Learning to transfer privileged information
V. Sharmanska, N. Quadrianto, and C. Lampert · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
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Curriculum learning of multiple tasks
A. Pentina, V. Sharmanska, and C. Lampert · 2015
Unifying distillation and privileged information
D. Lopez-Paz, L. Bottou, B. Schölkopf, and V. Vapnik · 2016
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Information bottleneck domain adaptation with privileged information for visual recognition
S. Motiian and G. Doretto · 2016
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Information bottleneck learning using privileged information for visual recognition
S. Motiian, M. Piccirilli, D. Adjeroh, and G. Doretto · 2016
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Predicting privileged information for height estimation
N. Sarafianos, C. Nikou, and I. A. Kakadiaris · 2016
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Learning from the mistakes of others: Matching errors in cross-dataset learning
V. Sharmanska and N. Quadrianto · 2016
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Exploiting privileged information for facial expression recognition
M. Vrigkas, C. Nikou, and I. A. Kakadiaris · 2016
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Subspace distribution alignment for unsupervised domain adaptation
B. Sun and K. Saenko · 2015
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Relative attribute SVM+ learning for age estimation
S. Wang, D. Tao, and J. Yang · 2015
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Classifier learning with hidden information
Z. Wang and Q. Ji · 2015
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Domain separation networks
K. Bousmalis, G. Trigeorgis, N. Silberman, D. Krishnan, and D. Erhan · 2016
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Cross modal distillation for supervision transfer
S. Gupta, J. Hoffman, and J. Malik · 2016
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Show me your body: Gender classification from still images
I. A. Kakadiaris, N. Sarafianos, and C. Nikou · 2016
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Fast algorithms for linear and kernel svm+
W. Li, D. Dai, M. Tan, D. Xu, and L. Van Gool · 2016
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Real-time action recognition with enhanced motion vector CNNs
B. Zhang, L. Wang, Z. Wang, Y. Qiao, and H. Wang · 2016
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Training group orthogonal neural networks with privileged information
Y. Chen, X. Jin, J. Feng, and S. Yan · 2017
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Domain adaptation for visual applications: A comprehensive survey
G. Csurka · 2017
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Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning
W. Ge and Y. Yu · 2017
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Teacher-student curriculum learning
T. Matiisen, A. Oliver, T. Cohen, and J. Schulman · 2017
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Adversarial discriminative domain adaptation
E. Tzeng, J. Hoffman, K. Saenko, and T. Darrell · 2017
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