I can has Cheezburger? A nonparanormal approach to combining textual and visual information for predicting and generating popular meme descriptions

NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Volumn , Issue , 2015, Pages 355-365

  Wang, William Yang ^a   Wen, Miaomiao ^a  

^a Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; STOCHASTIC SYSTEMS;

MULTI-MODAL APPROACH; POPULAR VOTE; SIMPLE PIPELINES; SOCIAL MEDIA; STOCHASTIC DEPENDENCIES; TEXT FEATURE; VISION FEATURES; VISUAL INFORMATION;

STOCHASTIC MODELS;

EID: 84960112591     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/n15-1039     Document Type: Conference Paper

References (56)

1. Joshua Albrecht and Rebecca Hwa. 2007. Regression for sentence-level mt evaluation with pseudo references. In Proceedings of ACL.
2. Yoav Artzi, Patrick Pantel, and Michael Gamon. 2012. Predicting responses to microblog posts. In Proceedings of NAACL-HLT.
3. Eytan Bakshy, Jake M Hofman, Winter A Mason, and Duncan J Watts. 2011. Everyone's an influencer: quantifying influence on twitter. In Proceedings of WSDM, pages 65-74. ACM.
4. Anna Bosch, Andrew Zisserman, and Xavier Munoz. 2007. Image classification using random forests and ferns.
5. Chih-Chung Chang and Chih-Jen Lin. 2011. Libsvm: a library for support vector machines. ACM TIST.
6. Xiaohong Chen and Yanqin Fan. 2006. Estimation of copula-based semiparametric time series models. Journal of Econometrics.
7. Xinlei Chen and C Lawrence Zitnick. 2014. Learning a recurrent visual representation for image caption generation. arXiv preprint arXiv:1411.5654.
8. David Christensen. 2005. Fast algorithms for the calculation of kendalls. Computational Statistics.
9. Dipanjan Das, Nathan Schneider, Desai Chen, and Noah A Smith. 2010. Probabilistic frame-semantic parsing. In Proceedings of NAACL-HLT.
10. Jacob Devlin, Rabih Zbib, Zhongqiang Huang, Thomas Lamar, Richard Schwartz, and John Makhoul. 2014. Fast and robust neural network joint models for statistical machine translation. In Proceedings of ACL.
11. Francis X Diebold, Todd A Gunther, and Anthony S Tay. 1997. Evaluating density forecasts.
12. Jesse Dodge, Amit Goyal, Xufeng Han, Alyssa Mensch, Margaret Mitchell, Karl Stratos, Kota Yamaguchi, Yejin Choi, Hal Daumé III, Alexander C Berg, et al. 2012. Detecting visual text. In Proceedings of the NAACL-HLT.
13. Jeff Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, and Trevor Darrell. 2014. Long-term recurrent convolutional networks for visual recognition and description. arXiv preprint arXiv:1411.4389.
14. Carsten Eickhoff, Arjen P. de Vries, and Kevyn Collins-Thompson. 2013. Copulas for information retrieval. In Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval.
15. Charles Elkan. 2003. Using the triangle inequality to accelerate k-means. In ICML, volume 3, pages 147-153.
16. Hao Fang, Saurabh Gupta, Forrest Iandola, Rupesh Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John Platt, et al. 2014. From captions to visual concepts and back. arXiv preprint arXiv:1411.4952.
17. Ali Farhadi, Mohsen Hejrati, Mohammad Amin Sadeghi, Peter Young, Cyrus Rashtchian, Julia Hockenmaier, and David Forsyth. 2010. Every picture tells a story: Generating sentences from images. In Computer Vision-ECCV 2010, pages 15-29. Springer.
18. Manuel Fernández-Delgado, Eva Cernadas, Senén Barro, and Dinani Amorim. 2014. Do we need hundreds of classifiers to solve real world classification problems? Journal of Machine Learning Research, 15:3133-3181.
19. Jenny Rose Finkel, Trond Grenager, and Christopher Manning. 2005. Incorporating non-local information into information extraction systems by gibbs sampling. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pages 363-370. Association for Computational Linguistics.
20. Alan Gelfand and Adrian Smith. 1990. Sampling-based approaches to calculating marginal densities. Journal of the American statistical association.
21. Zoubin Ghahramani, Barnabás Póczos, and Jeff Schneider. 2012. Copula-based kernel dependency measures. In Proceedings of the 29th International Conference on Machine Learning.
22. Abhinav Gupta, Praveen Srinivasan, Jianbo Shi, and Larry S Davis. 2009. Understanding videos, constructing plots learning a visually grounded storyline model from annotated videos. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages 2012-2019. IEEE.
23. Fang Han, Tuo Zhao, and Han Liu. 2012. Coda: High dimensional copula discriminant analysis. Journal of Machine Learning Research.
24. Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov. 2012. Improving neural networks by preventing coadaptation of feature detectors. arXiv preprint arXiv:1207.0580.
25. Micah Hodosh, Peter Young, and Julia Hockenmaier. 2013. Framing image description as a ranking task: Data, models and evaluation metrics. J. Artif. Intell. Res.(JAIR), 47:853-899.
26. Robert V Hogg and Allen Craig. 1994. Introduction to mathematical statistics.
27. Liangjie Hong, Ovidiu Dan, and Brian D Davison. 2011. Predicting popular messages in twitter. In Proceedings of WWW.
28. Harry Joe. 1997. Multivariate models and dependence concepts.
29. Andrej Karpathy and Li Fei-Fei. 2014. Deep visualsemantic alignments for generating image descriptions. Stanford University Technical Report.
30. Maurice Kendall. 1938. A new measure of rank correlation. Biometrika.
31. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems, pages 1097-1105.
32. Girish Kulkarni, Visruth Premraj, Sagnik Dhar, Siming Li, Yejin Choi, Alexander C Berg, and Tamara L Berg. 2011. Baby talk: Understanding and generating image descriptions. In Proceedings of the 24th CVPR. Citeseer.
33. Mirella Lapata. 2006. Automatic evaluation of information ordering: Kendall's tau. Computational Linguistics.
34. Han Liu, John Lafferty, and Larry Wasserman. 2009. The nonparanormal: Semiparametric estimation of high dimensional undirected graphs. The Journal of Machine Learning Research, 10:2295-2328.
35. Han Liu, Fang Han, Ming Yuan, John Lafferty, and Larry Wasserman. 2012. High-dimensional semiparametric gaussian copula graphical models. The Annals of Statistics.
36. Tomá?s Mikolov. 2012. Statistical language models based on neural networks. Ph.D. thesis, Ph. D. thesis, Brno University of Technology.
37. Margaret Mitchell, Xufeng Han, Jesse Dodge, Alyssa Mensch, Amit Goyal, Alex Berg, Kota Yamaguchi, Tamara Berg, Karl Stratos, and Hal Daumé III. 2012. Midge: Generating image descriptions from computer vision detections. In Proceedings of EACL.
38. Roger B Nelsen. 1999. An introduction to copulas. Springer Verlag.
39. Joakim Nivre, Johan Hall, Jens Nilsson, Atanas Chanev, Gülsen Eryigit, Sandra Kübler, Svetoslav Marinov, and Erwin Marsi. 2007. Maltparser: A languageindependent system for data-driven dependency parsing. Natural Language Engineering, 13(02):95-135.
40. Maxime Oquab, Leon Bottou, Ivan Laptev, Josef Sivic, et al. 2013. Learning and transferring mid-level image representations using convolutional neural networks.
41. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of ACL, pages 311-318. Association for Computational Linguistics.
42. Rahul A Parsa and Stuart A Klugman. 2011. Copula regression. Variance Advancing and Science of Risk.
43. Emanuel Parzen. 1962. On estimation of a probability density function and mode. The annals of mathematical statistics.
44. Michael Pitt, David Chan, and Robert Kohn. 2006. Efficient bayesian inference for gaussian copula regression models. Biometrika.
45. Berthold Schweizer and Abe Sklar. 1983. Probabilistic metric spaces.
46. Josef Sivic and Andrew Zisserman. 2003. Video google: A text retrieval approach to object matching in videos. In Proceedings of ICCV, pages 1470-1477. IEEE.
47. Abe Sklar. 1959. Fonctions de répartitionà n dimensions et leurs marges. Université Paris 8.
48. Richard Socher, Alex Perelygin, Jean Y Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proceedings of EMNLP, pages 1631-1642. Citeseer.
49. Chenhao Tan, Lillian Lee, and Bo Pang. 2014. The effect of wording on message propagation: Topic-and author-controlled natural experiments on twitter. In Proceedings of ACL.
50. Robert Tibshirani. 1996. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological), pages 267-288.
51. Kristina Toutanova, Dan Klein, Christopher D Manning, and Yoram Singer. 2003. Feature-rich part-of-speech tagging with a cyclic dependency network. In Proceedings of NAACL-HLT.
52. Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan. 2014. Show and tell: A neural image caption generator. arXiv preprint arXiv:1411.4555.
53. Stefan Wager, Sida Wang, and Percy Liang. 2013. Dropout training as adaptive regularization. In Advances in Neural Information Processing Systems, pages 351-359.
54. William Yang Wang and Zhenhao Hua. 2014. A semiparametric gaussian copula regression model for predicting financial risks from earnings calls. In Proceedings of ACL.
55. Sida Wang and Christopher Manning. 2013. Fast dropout training. In Proceedings of ICML.
56. Dani Yogatama, Michael Heilman, Brendan O'Connor, Chris Dyer, Bryan R Routledge, and Noah A Smith. 2011. Predicting a scientific community's response to an article. In Proceedings of EMNLP.