Transfer learning in a transductive setting

Advances in Neural Information Processing Systems

Volumn , Issue , 2013, Pages

  Rohrbach, Marcus ^a   Ebert, Sandra ^a   Schiele, Bernt ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; GRAPHIC METHODS; IMAGE CLASSIFICATION; SEMANTICS;

ACTIVITY RECOGNITION; EXTERNAL KNOWLEDGE; GRAPH-BASED LEARNING; LOCAL NEIGHBORHOODS; MANIFOLD STRUCTURES; SEMANTIC ATTRIBUTE; SEMI-SUPERVISED LEARNING; TRANSFER INFORMATION;

SUPERVISED LEARNING;

EID: 84899001511     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (35)

1. E. Bart & S. Ullman. Single-example learning of novel classes using representation by similarity. In BMVC, 2005.
2. A. Berg, J. Deng, & L. Fei-Fei. ILSVRC 2010. www.image-net.org/ challenges/LSVRC/2010/, 2010.
3. U. Blanke & B. Schiele. Remember and transfer what you have learned - recognizing composite activities based on activity spotting. In ISWC, 2010.
4. J. Choi, M. Rastegari, A. Farhadi, & L. S. Davis. Adding Unlabeled Samples to Categories by Learned Attributes. In CVPR, 2013.
5. S. Ebert, D. Larlus, & B. Schiele. Extracting Structures in Image Collections for Object Recognition. In ECCV, 2010.
6. R. Farrell, O. Oza, V. Morariu, T. Darrell, & L. S. Davis. Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance. In ICCV, 2011.
7. R. Fergus, Y. Weiss, & A. Torralba. Semi-supervised learning in gigantic image collections. NIPS 2009.
8. M. Fink. Object classification from a single example utilizing class relevance pseudo-metrics. In NIPS, 2004.
9. Y. Fu, T. M. Hospedales, T. Xiang, & S. Gong. Learning multi-modal latent attributes. TPAMI, PP(99), 2013.
10. P. Kankuekul, A. Kawewong, S. Tangruamsub, & O. Hasegawa. Online Incremental Attribute-based Zero-shot Learning. In CVPR, 2012.
11. C. Lampert, H. Nickisch, & S. Harmeling. Attribute-based classification for zero-shot learning of object categories. TPAMI, PP(99), 2013.
12. H.-T. Lin, C.-J. Lin, & R. C. Weng. A note on platt's probabilistic outputs for support vector machines. Machine Learning, 2007.
13. J. Liu, B. Kuipers, & S. Savarese. Recognizing human actions by attributes. In CVPR, 2011.
14. U. Luxburg. A tutorial on spectral clustering. Stat Comput, 17(4):395-416, 2007.
15. M. Maier, U. V. Luxburg, & M. Hein. Influence of graph construction on graph-based clustering measures. In NIPS, 2008.
16. T. Mensink, J. Verbeek, F. Perronnin, & G. Csurka. Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost. In ECCV, 2012.
17. Y. Moses, S. Ullman, & S. Edelman. Generalization to novel images in upright and inverted faces. Perception, 25:443-461, 1996.
18. A. Y. Ng, M. I. Jordan, & Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS, 2002.
19. M. Palatucci, D. Pomerleau, G. Hinton, & T. Mitchell. Zero-shot learning with semantic output codes. In NIPS, 2009.
20. S. J. Pan & Q. Yang. A survey on transfer learning. TKDE, 22:1345-59, 2010.
21. R. Raina, A. Battle, H. Lee, B. Packer, & A. Ng. Self-taught learning: Transfer learning from unlabeled data. In ICML, 2007.
22. M. Rohrbach, M. Regneri, M. Andriluka, S. Amin, M. Pinkal, & B. Schiele. Script data for attribute-based recognition of composite activities. In ECCV, 2012.
23. M. Rohrbach, M. Stark, & B. Schiele. Evaluating Knowledge Transfer and Zero-Shot Learning in a Large-Scale Setting. In CVPR, 2011.
24. M. Rohrbach, M. Stark, G. Szarvas, I. Gurevych, & B. Schiele. What Helps Where - And Why? Semantic Relatedness for Knowledge Transfer. In CVPR, 2010.
25. K. Saenko, B. Kulis, M. Fritz, & T. Darrell. Adapting visual category models to new domains. In ECCV, 2010.
26. V. Sharmanska, N. Quadrianto, & C. H. Lampert. Augmented Attribute Representations. In ECCV, 2012.
27. A. Shrivastava, S. Singh, & A. Gupta. Constrained Semi-Supervised Learning Using Attributes and Comparative Attributes. In ECCV, 2012.
28. J. Sivic, B. C. Russell, A. A. Efros, A. Zisserman, & W. T. Freeman. Discovering Object Categories in Image Collections. In ICCV, 2005.
29. S. Thrun. Is learning the n-th thing any easier than learning the first. In NIPS, 1996.
30. A. Torralba, K. Murphy, & W. Freeman. Sharing visual features for multiclass and multiview object detection. In CVPR, 2004.
31. D. Tran & A. Sorokin. Human activity recognition with metric learning. In ECCV, 2008.
32. M. Weber, M. Welling, & P. Perona. Towards automatic discovery of object categories. In CVPR, 2000.
33. D. Zhou, O. Bousquet, T. N. Lal, Jason Weston, & B. Schölkopf. Learning with Local and Global Consistency. In NIPS, 2004.
34. X. Zhu, Z. Ghahramani, & J. Lafferty. Semi-supervised learning using gaussian fields and harmonic functions. In ICML, 2003.
35. A. Zweig & D.Weinshall. Exploiting object hierarchy: Combining models from different category levels. In ICCV, 2007.