Beyond dataset bias: Multi-task unaligned shared knowledge transfer

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7724 LNCS, Issue PART 1, 2013, Pages 1-15

  Tommasi, Tatiana ^a,b   Quadrianto, Novi ^c   Caputo, Barbara ^a   Lampert, Christoph H ^d  

^a IDIAP RESEARCH INSTITUTE   (Switzerland)

^b EPFL   (Switzerland)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^d INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION TASKS; GENERALIZATION ABILITY; GENERALIZATION PERFORMANCE; GENERIC REPRESENTATION; IMAGE REPRESENTATIONS; KNOWLEDGE TRANSFER; LEARNING TECHNIQUES; MULTI-CLASS PROBLEMS;

ALGORITHMS;

KNOWLEDGE MANAGEMENT;

EID: 84875900597     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-37331-2_1     Document Type: Conference Paper

References (35)

1. Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. Comput. Vis. Image Underst. 106, 59-70 (2007)
2. Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge 2007 (VOC 2007) Results (2007), http://www.pascal-network.org/challenges/VOC/
3. Lampert, C.H., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between class attribute transfer. In: CVPR (2009)
4. Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: ImageNet: A Large-Scale Hierarchical Image Database. In: CVPR (2009)
5. Torralba, A., Efros, A.A.: Unbiased look at dataset bias. In: CVPR (2011)
6. Perronnin, F., Sánchez, J., Liu, Y.: Large-scale image categorization with explicit data embedding. In: CVPR (2010)
7. Stark, M.M., Riesenfeld, R.F.: Wordnet: An electronic lexical database. In: Eurographics Workshop on Rendering. MIT Press (1998)
8. Salakhutdinov, R., Torralba, A., Tenenbaum, J.: Learning to Share Visual Appearance for Multiclass Object Detection. In: CVPR (2011)
9. Blitzer, J., Crammer, K., Kulesza, A., Pereira, O., Wortman, J.: Learning bounds for domain adaptation. In: NIPS (2008)
10. Ben-david, S., Blitzer, J., Crammer, K., Sokolova, P.M.: Analysis of representations for domain adaptation. In: NIPS (2007)
11. Blitzer, J., McDonald, R., Pereira, F.: Domain adaptation with structural correspondence learning. In: EMNLP (2006)
12. Daumé III, H.: Frustratingly easy domain adaptation. In: ACL (2007)
13. Saenko, K., Kulis, B., Fritz, M., Darrell, T.: Adapting Visual Category Models to New Domains. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 213-226. Springer, Heidelberg (2010)
14. Gopalan, R., Li, R., Chellappa, R.: Domain adaptation for object recognition: An unsupervised approach. In: ICCV (2011)
15. Gong, B., Shi, Y., Sha, F., Grauman, K.: Geodesic flow kernel for unsupervised domain adaptation. In: CVPR (2012)
16. Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering 22, 1345-1359 (2010)
17. Jie, L., Tommasi, T., Caputo, B.: Multiclass transfer learning from unconstrained priors. In: ICCV (2011)
18. Evgeniou, T., Pontil, M.: Regularized multi-task learning. In: KDD (2004)
19. Kang, Z., Grauman, K., Sha, F.: Learning with whom to share in multi-task feature learning. In: ICML (2011)
20. Wang, X., Zhang, C., Zhang, Z.: Boosted multi-task learning for face verification with applications to web image and video search. In: CVPR (2009)
21. Vezhnevets, A., Buhmann, J.M.: Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning. In: CVPR (2010)
22. Quadrianto, N., Smola, A.J., Caetano, T.S., Vishwanathan, S.V.N., Petterson, J.: Multitask learning without label correspondences. In: NIPS (2010)
23. Parameswaran, S., Weinberger, K.: Large margin multi-task metric learning. In: NIPS (2010)
24. Leen, G.: Context assisted information extraction. PhD thesis, University of the West of Scotland (2008)
25. Jia, Y., Salzmann, M., Darrell, T.: Factorized latent spaces with structured sparsity. In: NIPS (2010)
26. Khosla, A., Zhou, T., Malisiewicz, T., Efros, A.A., Torralba, A.: Undoing the Damage of Dataset Bias. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part I. LNCS, vol. 7572, pp. 158-171. Springer, Heidelberg (2012)
27. Weinberger, K., Saul, L.: Distance metric learning for large margin nearest neighbor classification. Journal of Machine Learning Research 10, 207-244 (2009)
28. Goldberger, J., Roweis, S.T., Hinton, G.E., Salakhutdinov, R.: Neighbourhood components analysis. In: NIPS (2004)
29. Quadrianto, N., Lampert, C.H.: Learning multi-view neighborhood preserving projections. In: ICML (2011)
30. Kleiner, A., Rahimi, A., Jordan, M.I.: Random conic pursuit for semidefinite programming. In: NIPS (2010)
31. Lewis, A.S., Overton, M.L.: Nonsmooth optimization via quasi-newton methods. Math. Programming (to appear)
32. Microsoft Research Cambridge Object Recognition Image Database (2005), http://research.microsoft.com/en-us/downloads/
33. Krizhevsky, A.: Learning multiple layers of features from tiny images. Technical Report MSc thesis, University of Toronto, USA (2007)
34. Oliva, A., Torralba, A.: Modeling the shape of the scene: A holistic representation of the spatial envelope. IJCV 42, 145-175 (2001)
35. Gibbons, J.: Nonparametric Statistical Inference. Marcel Dekker, New York (1985)