Conference Publication

*** 2017

Y. S. Wang,  X. J. Deng, S. B. Pu, Z.H. Huang, Residual Convolutional CTC Networks for Automatic Speech Recognition,

*** 2016

H. N. Yu, J. Wang, Z. H. Huang, Y. Yang, and W. Xu, Video Paragraph Captioning using Hierarchical Recurrent Neural Networks, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016

J. Wang, Y. Yang, J. H. Mao, Z. H. Huang, C. Huang, and W. Xu, CNN-RNN: A Unified Framework for Multi-label Image Classification, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016

*** 2015

Z. H. Huang, W. Xu, and K. Yu, Bidirectional LSTM-CRF Models for Sequence Tagging, arXiv:1508.01991, 2015. Penn Treebank part-of-speech tagging state of the art accuracy: 97.55%.

​H. Y. Gao, J. H. Mao, J. Zhou, Z. H. Huang, L. Wang, and W. Xu, Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question Answering, NIPS, 2015. News report click here

J. H. Mao, W. Xu, Y. Yang, J. Wang, Z. H. Huang and A. Yuille, Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images, [arXiv: 1504.06692], 2015.

J. H. Mao, W. Xu, Y. Yang,  J. Wang, Z. H. Huang, and A. Yuille, Deep captioning with multimodal recurrent neural networks (m-RNN), International Conference on Learning Representations (ICLR) 2015.

*** 2014

Z. H. Huang, G. Zweig and B. Dumoulin, Cache based Recurrent Neural Network Language Model Inference for First Pass Speech Recognition,  IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014.

Dong Yu, Adam Eversole, Mike Seltzer, Kaisheng Yao, Zhiheng Huang, Brian Guenter, Oleksii Kuchaiev, Yu Zhang, Frank Seide, Huaming Wang, Jasha Droppo, Geoffrey Zweig, Chris Rossbach, Jon Currey, Jie Gao, Avner May, Andreas Stolcke, Malcolm Slaney, “An Introduction to Computational Networks and the Computational Network Toolkit“, Microsoft Technical Report MSR-TR-2014-112, 2014.

*** 2013

Z. H.  Huang, G. Zweig, M. Levit, B. Dumoulin, B. Oguz and S. Chang, Accelerating Recurrent Neural Network Training via Two Stage Classes and Parallelization, in Automatic Speech Recognition and Understanding (ASRU), 2013.

*** 2012

Z. H. Huang, Y. Chang, B. Long, J. F. Crespo, A. L. Dong, S. Keerthi and S. L. Wu, Iterative Viterbi A* algorithm for k-best sequential decoding, in The 50th Annual Meeting of the Association for Computational Linguistics (ACL), 2012.

*** 2009

Z. H. Huang, M. Thint and A. Celikyilmaz, Investigation of question classifier in question answering, inConference on Empirical Methods in Natural Language Processing (EMNLP), 2009.

Z. H. Huang, M. Thint, A. Celikyilmaz, G. Zeng and W. Xu ,  Accurate semantic class classifier for coreference resolution,  in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2009.

A. Celikyilmaz, M. Thint and Z. H. Huang, A graph-based semi-supervised learning for question-answering, in the 47th Annual Meeting of the Association for Computational Linguistics (ACL), 2009.

Z. Qin, M. Thint, and Z. H. Huang,  Ranking answers by hierarchical topic models, in The Twenty Second International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE), 2009.

*** 2008

Z. H. Huang, M. Thint and Z. Qin, Question Classification using Head Words and their Hypernyms, in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2008.

*** 2007

Z. H. Huang, M. Nikravesh, B. Azvine and T. D. Gedeon, Weighted Pattern Trees: A Case Study with Customer Satisfaction Dataset, vol. 4529 of Foundations of Fuzzy Logic and Soft Computing, pp. 395 — 406, Springer Berlin/Heidelberg, 2007.

*** 2006

Z. H. Huang and T. D. Gedeon, Pattern trees,  in Proc. of IEEE International Conference on Fuzzy Systems, pp.
1784-1791, 2006.

Z. H. Huang and T. D. Gedeon, Information retrieval estimation via fuzzy probability, in Proc. World Automation Congress, 2006.

*** 2005

Z. H. Huang and Q. Shen, Preserving piece-wise linearity in fuzzy interpolation, In Proc. of the 2005 UK Workshop on Computational Intelligence, 2005.

Z. H. Huang and Q. Shen,  Transformation based interpolation with generalized representative values, in Proc. of IEEE International Conference on Fuzzy Systems, pp. 821-826, 2005.

*** 2004

Z. H. Huang and Q. Shen, Fuzzy interpolation with generalized representative values, In Proc. of the 2004 UK
Workshop on Computational Intelligence, pp. 161-171, 2004.

Z. H. Huang and Q. Shen, Scale and move  transformation-based fuzzy interpolative reasoning: a revisit, in Proc. of IEEE International Conference on Fuzzy Systems, vol. 2, pp. 623-628, 2004.

*** 2003

Z. H. Huang and Q. Shen, A new fuzzy interpolative reasoning method based on center of gravity, in Proc. of IEEE International Conference on Fuzzy Systems, vol. 1, pp. 25-30, 2003.

Journal Publication

Z. H. Huang, T. D. Gedeon, and M. Nikravesh, Pattern trees induction: a new machine learning method, in IEEE Trans. on Fuzzy Systems}, vol. 16, no. 3, pp. 958 – 970, August 2008.

Z. H. Huang and Q. Shen, Fuzzy interpolation and extrapolation: a practical approach,” in IEEE Trans. on Fuzzy Systems, vol. 16, no. 1, pp. 13 – 28, Feb 2008.

Z. H. Huang and Q. Shen,  Fuzzy interpolation reasoning via scale and move transformations, in IEEE Trans. on Fuzzy Systems, vol. 14, no. 2, pp. 340 – 359, April 2006.

Book Chapter

Z. H. Huang, M. Nikravesh, T. D. Gedeon, and B. Azvine, Pattern trees: an effective machine learning approach, Studies in Fuzziness and Soft Computing, Springer Berlin/Heidelberg, vol. 218, pp. 399 – 433, 2008.