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Zhifei Li |
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Ph.D. Student |
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Office: CSEB 322 |
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Email: zhifei.work@gmail.com |
Research Interests
Natural Language Processing (current focus)
I am interested in applying machine learning methods (mainly sequence/structured model) on large-scale NLP applications such as Machine Translation and Language Modeling. Due to the large scale of the training data and the model search space, compact data structures (for model representation) and efficient algorithms (for model inference and learning) are essential. Also, due to the complex dependency among the model parameters, a discriminative feature-based framework is more flexible than a generative model. Currently, I am working on large-scale discriminative training for machine translation system (e.g., translation between Chinese and English).
Networking and
Distributed Systems
I am also interested in system-oriented research on computer networks. Before coming to JHU, I have done some work in wireless networks. In particular, during 1999-2002, I have worked at MobileSoft for several commercial projects related to WAP and Bluetooth. During 2002-2004 at NTU, I have worked on Medium Access Control issues in IEEE 802.11-based wireless networks. Here are some of my publications in this area.
Applied Algorithms
I was also very interested in applying algorithmic/theoretical methods in some fascinating applications. I found the following theoretical areas, Distributed Algorithms, Game Theory, Graph Algorithms, and Online Algorithms, are of great interests. The application problems that I was interested in are Wireless Networks, P2P, Web Search Ranking, and Reputation Systems.
Publications (on Natural Language
Processing):
Machine Translation:
First- and Second-order Expectation Semirings with Applications to Minimum-Risk Training on Translation Forests. To appear in EMNLP 2009.
Variational Decoding for Statistical Machine Translation. To appear in ACL 2009.
Zhifei Li and Sanjeev Khudanpur. Forest Reranking for Machine Translation with the Perceptron Algorithm. To appear in the GALE book chapter on "MT from text", 2009.
Jason Smith, Damianos Karakos, Zhifei Li, Jason Eisner and Sanjeev Khudanpur. Novel System Combination Approaches for MT. To appear in the GALE book chapter on "MT from text", 2009.
Zhifei Li and Sanjeev Khudanpur. Efficient Extraction of Oracle-best Translations from Hypergraphs. In Proceedings of NAACL 2009 (short paper).
Zhifei Li and Sanjeev
Khudanpur. Large-scale
Discriminative n-gram Language Models for Statistical Machine Translation.
In Proceedings of AMTA 2008.
Zhifei Li and Sanjeev
Khudanpur. A
Scalable Decoder for Parsing-based Machine Translation with Equivalent Language
Model State Maintenance. In Proceedings of ACL SSST 2008.
Zhifei Li and David
Yarowsky. Unsupervised
Translation Induction for Chinese Abbreviations using Monolingual Corpora.
In Proceedings of ACL 2008.
Information Extraction:
Zhifei Li and David
Yarowsky. Mining
and Modeling Relations between Formal and Informal Chinese Phrases from Web
Corpora. In Proceedings of EMNLP 2008.
Training and test data: download
Spoken Dialogue Management:
Zhifei Li, Patrick
Nguyen, and Geoffrey Zweig. Optimal
Dialog in Consumer-Rating Systems using a POMDP Framework. In Proceedings
of ACL SIGdial 2008.
Joshua Decoder Related:
Software: download
Zhifei Li, Chris Callison-Burch, Chris Dyer, Juri Ganitkevitch, Sanjeev
Khudanpur, Lane Schwartz, Wren Thornton, Jonathan Weese and Omar Zaidan, 2009.
Demonstration of Joshua: An Open Source Toolkit for Parsing-based Machine
Translation. To appear in ACL 2009 (demo).
Zhifei Li, Chris Callison-Burch, Chris Dyer, Juri Ganitkevitch, Sanjeev
Khudanpur, Lane Schwartz, Wren Thornton, Jonathan Weese and Omar Zaidan, 2009.
Joshua: An Open
Source Toolkit for Parsing-based Machine Translation. In Proceedings of the
Workshop on Statistical Machine Translation (WMT09).
Publications (on wireless
networking)
Teaching (TA)
Introduction to Algorithms
(Fall of 2005, Prof. Baruch Awerbuch)
Computer
Networks Fundamentals (Spring of 2005 and 2006, Prof. Gerald M. Masson)
Computer
Organization Fundamentals (Fall of 2004, Prof. Gerald M. Masson)