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Ming Tan
2010 – today
- 2012
[j15]Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang: A Scalable Distributed Syntactic, Semantic, and Lexical Language Model. Computational Linguistics 38(3): 631-671 (2012)- [c14]Jingshan Huang, Xingyu Lu, Dejing Dou, William T. Gerthoffer, Jiangbo Dang, Judith A. Blake, Ming Tan: An ontology-based MicroRNA knowledge sharing and acquisition framework. BIBM Workshops 2012: 740-747
- 2011
- [c13]Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang: A Large Scale Distributed Syntactic, Semantic and Lexical Language Model for Machine Translation. ACL 2011: 201-210
- 2010
- [j14]Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, Ronald B. Gartenhaus: Kernel based methods for accelerated failure time model with ultra-high dimensional data. BMC Bioinformatics 11: 606 (2010)
- [j13]Zhenqiu Liu, Shili Lin, Ming Tan: Sparse Support Vector Machines with L_{p} Penalty for Biomarker Identification. IEEE/ACM Trans. Comput. Biology Bioinform. 7(1): 100-107 (2010)
- [c12]Jingshan Huang, Ming Tan, Dejing Dou, Lei He, Christopher Townsend, Patrick J. Hayes: Ontology for MicroRNA Target prediction in human cancer. BCB 2010: 472-474
2000 – 2009
- 2009
- [j12]Guo-Liang Tian, Kai Wang Ng, Kai-Can Li, Ming Tan: Non-iterative sampling-based Bayesian methods for identifying changepoints in the sequence of cases of Haemolytic uraemic syndrome. Computational Statistics & Data Analysis 53(9): 3314-3323 (2009)
- [j11]Zhenqiu Liu, Ronald B. Gartenhaus, Xue-Wen Chen, Charles D. Howell, Ming Tan: Survival Prediction and Gene Identification with Penalized Global AUC Maximization. Journal of Computational Biology 16(12): 1661-1670 (2009)
- [j10]Guo-Liang Tian, Hong-Bin Fang, Ming Tan, Hong Qin, Man-Lai Tang: Uniform distributions in a class of convex polyhedrons with applications to drug combination studies. J. Multivariate Analysis 100(8): 1854-1865 (2009)
- 2008
- [j9]Zhenqiu Liu, Ronald B. Gartenhaus, Ming Tan, Feng Jiang, Xiaoli Jiao: Gene and pathway identification with Lp penalized Bayesian logistic regression. BMC Bioinformatics 9 (2008)
- [j8]Guo-Liang Tian, Man-Lai Tang, Hong-Bin Fang, Ming Tan: Efficient methods for estimating constrained parameters with applications to regularized (lasso) logistic regression. Computational Statistics & Data Analysis 52(7): 3528-3542 (2008)
- [j7]Guo-Liang Tian, Kai Wang Ng, Ming Tan: EM-type algorithms for computing restricted MLEs in multivariate normal distributions and multivariate t-distributions. Computational Statistics & Data Analysis 52(10): 4768-4778 (2008)
- 2007
- [j6]Man-Lai Tang, Kai Wang Ng, Guo-Liang Tian, Ming Tan: On improved EM algorithm and confidence interval construction for incomplete r. Computational Statistics & Data Analysis 51(6): 2919-2933 (2007)
- 2006
- [j5]Ming Tan, Guo-Liang Tian, Kai Wang Ng: Hierarchical models for repeated binary data using the IBF sampler. Computational Statistics & Data Analysis 50(5): 1272-1286 (2006)
- [j4]Zhenqiu Liu, Shili Lin, Ming Tan: Genome-Wide Tagging SNPs with Entropy-Based Monte Carlo Method. Journal of Computational Biology 13(9): 1606-1614 (2006)
- [c11]Bocheng Zhong, Jianghong Han, Zhaofang Du, Yuan Ming, Ming Tan: Game Based Flow Rate Control for Networks. ICICIC (1) 2006: 401-404
- 2001
- [c10]Steve Gallant, Gregory Piatetsky-Shapiro, Ming Tan: Value-based data mining and web mining for CRM. KDD Tutorials 2001
- 2000
- [c9]Ming Tan, Johnson Lee, Hao Xu, Joshua Introne, Christopher J. Matheus: Wireless usage analysis for capacity planning and beyond: a data warehouse approach. NOMS 2000: 905-917
1990 – 1999
- 1999
- [c8]Ming Tan, Hao Xu, Johnson Lee: DART: A Decision Support System for Cellular Networks Usage Analysis. IC-AI 1999: 479-485
- 1996
- [c7]Ming Tan, Carol Lafond, Gabriel Jakobson, Gary Young: Supporting Performance and Configuration Management of GTE Cellular Networks. AAAI/IAAI, Vol. 2 1996: 1556-1563
- 1993
- [j3]Ming Tan: Cost-Sensitive Learning of Classification Knowledge and Its Applications in Robotics. Machine Learning 13: 7-33 (1993)
- [c6]Ming Tan: Multi-Agent Reinforcement Learning: Independent versus Cooperative Agents. ICML 1993: 330-337
- 1991
- [j2]Ming Tan, Jeffrey C. Schlimmer: A cost-sensitive machine learning method for the approach and recognize task. Robotics and Autonomous Systems 8(1-2): 31-45 (1991)
- [c5]Ming Tan: Cost-Sensitive Reinforcement Learning for Adaptive Classification and Control. AAAI 1991: 774-780
- [c4]Ming Tan: Learning a Cost-Sensitive Internal Representation for Reinforcement Learning. ML 1991: 358-362
- 1990
- [c3]Ming Tan, Jeffrey C. Schlimmer: Two Case Studies in Cost-Sensitive Concept Acquisition. AAAI 1990: 854-860
1980 – 1989
- 1989
- [c2]Ming Tan, Jeffrey C. Schlimmer: Cost-Sensitive Concept Learning of Sensor Use in Approach ad Recognition. ML 1989: 392-395
- 1988
- [c1]Ming Tan, Larry J. Eshelman: Using Weighted Networks to Represent Classification Knowledge in Noisy Domains. ML 1988: 121-134
- 1987
- [j1]Larry J. Eshelman, Damien Ehret, John P. McDermott, Ming Tan: MOLE: A Tenacious Knowledge-Acquisition Tool. International Journal of Man-Machine Studies 26(1): 41-54 (1987)
Coauthor Index
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last updated on 2013-03-07 21:27 CET by the dblp team