Transductive multi-label zero-shot learning

BMVC 2014 - Proceedings of the British Machine Vision Conference 2014

Volumn , Issue , 2014, Pages

  Fu, Yanwei ^a   Yang, Yongxin ^a   Hospedales, Timothy ^a   Xiang, Tao ^a   Gong, Shaogang ^a  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; REGRESSION ANALYSIS; SEMANTICS; VECTOR SPACES;

COMPOSITIONALITY; MULTI-OUTPUT; REGRESSION MODEL; SEMANTIC LAYER; SEMANTIC REPRESENTATION; TRAINING DATA; TRANSDUCTIVE LEARNING; WORD VECTORS;

LEARNING SYSTEMS;

EID: 85087240380     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/c.28.7     Document Type: Conference Paper

References (34)

1. I. Biederman. Recognition by components - a theory of human image understanding. Psychological Review, 1987.
2. Chih-Chung Chang and Chih-Jen Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
3. Ke Chen, Shaogang Gong, Tao Xiang, and Chen Chang Loy. Cumulative attribute space for age and crowd density estimation. In CVPR, 2013.
4. Qing Da, Yang Yu, and Zhi-Hua Zhou. Learning with augmented class by exploiting unlabeled data. In AAAI, 2014.
5. Andre Elisseeff and Jason Weston. A kernel method for multi-labelled classification. In NIPS, 2001.
6. Andrea Frome, Greg S. Corrado, Jon Shlens, Samy Bengio, Jeffrey Dean, Marc Aurelio Ranzato, and Tomas Mikolov. Devise: A deep visual-semantic embedding model. In NIPS, 2013.
7. Yanwei Fu, Timothy M. Hospedales, Tao Xiang, and Shaogang Gong. Attribute learning for understanding unstructured social activity. In ECCV, 2012.
8. Yanwei Fu, Timothy M. Hospedales, Tao Xiang, and Shaogang Gong. Learning multimodal latent attributes. TPAMI, 2013.
9. Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Zhengyong Fu, and Shaogang Gong. Transductive multi-view embedding for zero-shot recognition and annotation. In ECCV, 2014.
10. Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong, and Yuan Yao. Interestingness prediction by robust learning to rank. In ECCV, 2014.
11. Michael Grubinger. Analysis and Evaluation of Visual Information Systems Performance. PhD thesis, School of Computer Science and Mathematics, Faculty of Health, Engineering and Science, Victoria University, 2007.
12. Bharath Hariharan, S. V. Vishwanathan, and Manik Varma. Efficient max-margin multi-label classification with applications to zero-shot learning. Mach. Learn., 2012.
13. Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer New York Inc., 2009.
14. Eric H. Huang, Richard Socher, Christopher D. Manning, and Andrew Y. Ng. Improving word representations via global context and multiple word prototypes. In ACL, 2012.
15. Feng Kang, Rong Jin, and Rahul Sukthankar. Correlated label propagation with application to multi-label learning. In CVPR, 2006.
16. Xiangnan Kong, M.K. Ng, and Zhi-Hua Zhou. Transductive multilabel learning via label set propagation. Knowledge and Data Engineering, IEEE Transactions on, 2013.
17. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
18. Christoph H. Lampert, Hannes Nickisch, and Stefan Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
19. Christoph H. Lampert, Hannes Nickisch, and Stefan Harmeling. Attribute-based classification for zero-shot visual object categorization. IEEE TPAMI, 2013.
20. Ryan Layne, Timothy M. Hospedales, and Shaogang Gong. Re-id: Hunting attributes in the wild. In BMVC, 2014.
21. Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. Efficient estimation of word representation in vector space. In Proceedings of Workshop at ICLR, 2013.
22. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. Distributed representations of words and phrases and their compositionality. In NIPS, 2013.
23. Aude Oliva and Antonio Torralba. Modeling the shape of the scene: A holistic representation of the spatial envelope. IJCV, 42, 2001.
24. Mark Palatucci, Geoffrey Hinton, Dean Pomerleau, and Tom M. Mitchell. Zero-shot learning with semantic output codes. In NIPS, 2009.
25. Anastasia Pentina and Christoph H. Lampert. A pac-bayesian bound for lifelong learning. In ICML, 2014.
26. Ali Sharif Razavian, Josephine Sullivan, and Stefan Carlsson. Cnn features off-theshelf : an astounding baseline for recognition. arXiv:1403.6382v1, 2014.
27. Marcus Rohrbach, Michael Stark, and Bernt Schiele. Evaluating knowledge transfer and zero-shot learning in a large-scale setting. In CVPR, 2012.
28. Pierre Sermanet, David Eigen, Xiang Zhang, Michael Mathieu, Rob Fergus, and Yann LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. In ICLR, 2014.
29. Viktoriia Sharmanska, Novi Quadrianto, and Christoph H. Lampert. Augmented attribute representations. In ECCV, 2012.
30. Richard Socher, Milind Ganjoo, Hamsa Sridhar, Osbert Bastani, Christopher D. Manning, and Andrew Y. Ng. Zero-shot learning through cross-modal transfer. In NIPS, 2013.
31. Le Wu and Min-Ling Zhang. Multi-label classification with unlabeled data: An inductive approach. In ACML, pages 197-212, 2013.
32. Min-Ling Zhang and Zhi-Hua Zhou. Ml-knn: A lazy learning approach to multi-label learning. Pattern Recognition, 2007.
33. Min-Ling Zhang and Zhi-Hua Zhou. A review on multi-label learning algorithms. IEEE Transactions on Knowledge and Data Engineering, page 1, 2013.
34. Zhi-Hua Zhou and Zhao-Qian Chen. Hybrid decision tree. Knowledge-Based Systems, 15(8):515-528, 2002.