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陳定立    Ting-Li Chen

Institute of Statistical Science
Academia Sinica
Taipei 11529, Taiwan

Tel: 886-2-27875626
FAX : 886-2-27886833


Research Interests

My research interests include Markov chain Monte Carlo methods, image processing and analysis, pattern recognition, and clustering and classification.


Ph.D., 2005, Applied Mathematics, Brown University
M.S., 1996, Mathematics, National Taiwan University
B.S., 1994, Mathematics, National Taiwan University


Associate Research Fellow, 2014-present, Institute of Statistical Science, Academia Sinica
Assistant Research Fellow, 2006-
2014, Institute of Statistical Science, Academia Sinica
Algorithm Engineer, 2004-2006, Mathematical Technologies Inc, Providence, U.S.A.

Selected Publications

Y.-S. Chin and T.-L. Chen* (2016). Minimizing variable selection criteria by Markov chain Monte Carlo, Computational Statistics, 31(4): 1263-1286.

T.-L. Chen*, H. Fujisawa, S.-Y. Huang and C.-R. Hwang (2016). On the weak convergence and central limit theorem of blurring and nonblurring processes with application to robust location Estimation, Journal of Multivariate Analysis, 143: 165-184.

S.-Y. Shiu and T.-L. Chen* (2016). On the strengths of the self-updating process clustering algorithm, Journal of Statistical Computation and Simulation, 86(5): 1010-1031.

S.-Y. Shiu and T.-L. Chen* (2015). On the rate of convergence of the Gibbs sampler for the 1-D Ising model by geometric bound, Statistics & Probability Letters, 105: 14-19.

T.-L. Chen (2015). “On the Convergence and Consistency of the Blurring Mean-Shift Process, Annals of the institute of Statistical Matheematics.67(1): 157-176.

T.-L. Chen, D.-N. Hsieh, H. Hung, I-P. Tu*, P.-S. Wu, Y.-M. Wu, W.-H. Chang* and S.-Y. Huang (2014). “γ-SUP: a clustering algorithm for cryo-electron microscopy images of asymmetric particles,” Annals of Applied Statistics, 8(1): 259-285.

T.-L. Chen* and S. Geman (2014). “Image warping using radial basis functions, Journal of Applied Statistics, 41(2): 242-258.

T.-L. Chen (2013), “Optimal Markov chain Monte Carlo sampling.” WIREs Comp Stat. 5(5): 341-348.

T.-L. Chen* and C.-R. Hwang. (2013). “Accelerating reversible Markov chains.” Statistics & Probability Letters, 83(9): 1956-1962.

T.-L. Chen*, W.-K. Chen, C.-R. Hwang and H.-M. Pai (2012). “On the optimal transition matrix for MCMC sampling.” SIAM Journal on Control and Optimization, 50(5): 2743-2762.

T.-L. Chen and S. Geman* (2008). On the Minimum Entropy of a Mixture of Unimodal and Symmetric Distributions, IEEE Tran. Information Theory, 54(7): 3166-3174.

T.-L. Chen* and S.-Y. Shiu (2007). A New Clustering Algorithm Based on Self-Updating Process,” In JSM Proceedings, Statistical Computing Section, Salt Lake City, Utah; American Statistical Association, pp. 2034-2038.

A. Amarasingham, T.-L. Chen, S. Geman, M. Harrison and D. Sheinberg (2006). Spike Count Reliability and the Poisson Hypothesis, The Journal of Neuroscience 26(3): 801-809.

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