Computer Science, Machine Learning, Language Technologies, Computational Biology | School of Computer Science | Carnegie Mellon

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Research area :
Statistical genetics | Evolutionary & Regulatory genomics | Systems Biology | Structural Biology
Graphical models | Non-parametric Bayesian | Mixture models & topic models | Graph & network modelling & learning | Structured I/O learning | Clustering, classification and metric learning | Active and transductive learning | Variational methods | Miscellaneous

2009:

M. Kolar, L. Song, A. Ahmed, and E. P. Xing, Estimating Time-Varying Networks to appear, Annals of Applied Statistics, 2009. (earlier version appeared in arXiv:0812.5087)
E.P. Xing, W. Fu, and L. Song, A State-Space Mixed Membership Block model for Dynamic Network Tomography to appear, Annals of Applied Statistics, 2009. (earlier version appeared in arXiv:0901.0135)
M. Kolar, L. Song and E. P. Xing, Sparsistent Learning of Varying-coefficient Models with Structural Changes, Proceeding of the 23rd Neural Information Processing Systems, (NIPS 2009).
L. Song, M. Kolar and E. P. Xing, Time-Varying Dynamic Bayesian Networks Proceeding of the 23rd Neural Information Processing Systems, (NIPS 2009).
X. Yang, S. Kim and E. P. Xing, Heterogeneous Multitask Learning with Joint Sparsity Constraints Proceeding of the 23rd Neural Information Processing Systems, (NIPS 2009).
S. Kim and E. P. Xing, Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity Manuscript, arXiv:0909.1373, communicated September 2009.
S. Hanneke, W. Fu and E. P. Xing, Discrete Temporal Models of Social Networks, Manuscript, arXiv:0908.1258, communicated August 2009.
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M. Kolar and E. P. Xing, Sparsistent Estimation of Time-Varying Discrete Markov Random Fields, Manuscript, arXiv:0907.2337, communicated July 2009.
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J. Zhu and E. P. Xing, Maximum Entropy Discrimination Markov Networks, Manuscript, arXiv:0901.2730, communicated January 2009.
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Seyoung Kim and Eric P. Xing, Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network, PLoS Genetics (to appear).
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Amr Ahmed and Eric P. Xing, TESLA: Recovering Time-Varying Networks of Dependencies in Social and Biological Studies, Proc. Natl. Acad. Sci. USA (2009, in press).
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Steve Hanneke, Theoretical Foundations of Active Learning Ph.D. Thesis, Carnegie Mellon University, Pittsburgh, April 2009
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Jun Zhu, Amr Ahmed and Eric P. Xing, MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification, Proceedings of the 26th International Conference on Machine Learning (ICML 2009)
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Jun Zhu and Eric P. Xing, On the Primal and Dual Sparsity in Markov Networks, Proceedings of the 26th International Conference on Machine Learning (ICML 2009)
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Wenjie Fu, Le Song and Eric P. Xing, Dynamic Mixed Membership Block Model for Evolving Networks, Proceedings of the 26th International Conference on Machine Learning (ICML 2009)
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Andre Martins, Noah Smith and Eric P. Xing, Polyhedral Outer Approximations with Application to Natural Language Parsing, Proceedings of the 26th International Conference on Machine Learning (ICML 2009)
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Andre Martins, Noah Smith and Eric P. Xing, Concise Integer Linear Programming Formulations for Dependency Parsing, Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics (ACL 2009)
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Jun Zhu, Eric P. Xing, and Bo Zhang, Primal Sparse Max-Margin Markov Networks, Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2009)
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Amr Ahmed, Eric P. Xing, William Cohen, and Robert Murphy, Structured Correspondence Topic Models for Mining Captioned Figures in Biological Literature, Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2009)
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Seyoung Kim, Kyung-Ah Sohn and Eric P. Xing, A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network, Proceedings of the 16th International Conference on Intelligent Systems for Molecular Biology (ISMB 2009), Bioinformatics 25(12):i204-i212.
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Le Song, Mladen Kolar and Eric P. Xing, KELLER: Estimating Time-Evolving Interactions Between Genes, Proceedings of the 16th International Conference on Intelligent Systems for Molecular Biology (ISMB 2009)
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Wenjie Fu, Pradipta Ray and Eric P. Xing, DISCOVER: A feature-based discriminative method for motif search in complex genomes, Proceedings of the 16th International Conference on Intelligent Systems for Molecular Biology (ISMB 2009)
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Suyash Shringarpure and Eric P. Xing, mStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations, Genetics, Vol 182, issue 2, 2009.
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Steve Hanneke and Eric P. Xing, Network Completion and Survey Sampling, Proceedings of the 12th International Conference on Artifical Intelligence and Statistics (AISTAT 2009)
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Kyung-Ah Sohn and Eric P. Xing, A Hierarchical Dirichlet Process Mixture Model For Haplotype Reconstruction From Multi-Population Data, Annals of Applied Statistics, 2009
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Andre Martins, Mario Figueiredo, Pedro Aguiar, Noah A. Smith, and Eric P. Xing, Nonextensive Entropic Kernels, Journal of Machine Learning Research, 2009
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Jun Zhu and Eric P. Xing, Maximum Entropy Discrimination Markov Networks, arXiv, communicated January 2009
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2008:

Amr Ahmed, Le Song, and Eric Xing, Time-Varying Networks: Recovering Temporally Rewiring Genetic Networks During the Life Cycle of Drosophila melanogaster , arXiv, communicated December 2008
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Wenjie Fu, Le Song, and Eric Xing, A State-Space Mixed Membership Blockmodel for Dynamic Network Tomography , arXiv, communicated December 2008
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Mladen Kolar, Le Song, and Eric Xing, Estimating Time-Varying Networks , arXiv, communicated December 2008
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Seyoung Kim, Kyung-Ah Sohn, Eric Xing, A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network, arXiv, communicated November 2008
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Mladen Kolar, Eric Xing, Improved Estimation of High-dimensional Ising Models, arXiv, communicated November 2008
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André F.T. Martins, Dipanjan Das, Noah A. Smith, Eric P. Xing, Stacking Dependency Parsers, Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP 2008)
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Jun Zhu, Eric Xing, Bo Zhang, Partially Observed Maximum Entropy Discrimination Markov Networks., Proceeding of the 22nd Neural Information Processing Systems (NIPS 2008)
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Edo Airoldi, David Blei, Steve Fienberg, Eric Xing, Mixed Membership Stochastic Blockmodel, Proceeding of the 22nd Neural Information Processing Systems (NIPS 2008)
Journal version here.
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Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric Xing, Training Hierarchical Feed-forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks. Proceeding of the 10th European Conference of Computer Vision (ECCV 2008)
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W.-H. Lin, E. P. Xing, and A. Hauptmann, A Joint Topic and Perspective Model for Ideological Discourse, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 08)
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R. Nallapati, A. Ahmed, E. P. Xing, and W. Cohen, Sparse Feature Joint Latent Topic Models for text and citations, Proceedings of The Fourteen ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (KDD 2008)
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S. Kim and E. P. Xing, Sparse Feature Learning in High-Dimensional Space via Block Regularized Regression, Proceedings of the 24th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI 2008)
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M.-F. Balcan, S. Hanneke, J. Wortman, The True Sample Complexity of Active Learning, Proceedings of the 21st Annual Conference on Learning Theory (COLT 2008)
Winner of the Mark Fulk Best Paper Award
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J. Zhu, E. P. Xing, B. Zhang, Laplace Maximum Margin Markov Networks, Proceedings of the 25th International Conference on Machine Learning (ICML 2008)
Longer version available as CMU-MLD Technical Report 08-104
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S. Shringarpure and E. P. Xing, mStruct: A New Admixture Model for Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations, Proceedings of the 25th International Conference on Machine Learning (ICML 2008)
Longer version available as CMU-MLD Technical Report 08-105
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A. Martins, M. Figueiredo, P. Aguiar, N. A. Smith and E. P. Xing, Nonextensive Entropic Kernels, Proceedings of the 25th International Conference on Machine Learning (ICML 2008)
Longer version available as CMU-MLD Technical Report 08-106
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P. Ray, S. Shringarpure, M. Kolar and E. P. Xing, CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing, PLoS Computational Biology (2008), Vol 4 (6), June 2008
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E. Airoldi, D. Blei, S. Fienberg and E. P. Xing, Mixed Membership Stochastic Blockmodels, Journal of Machine Learning Research (2008), Vol 4, Sep 2008
Conference version here.
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F. Guo, L. Li, C. Faloutsos and E. P. Xing, C-DEM: A Multi-Modal Query System for Drosophila Embryo Databases, Proceedings of The 34th International Conference on Vary Large Data Bases (VLDB2008)
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A.Ahmed and E. P. Xing, Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process, Proceedings of The Eighth SIAM International Conference on Data Mining (SDM 2008)
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Z. Guo, Z. Zhang, E. P. Xing and C. Faloutsos, Semi-supervised Learning Based on Semiparametric Regularization, Proceedings of The Eighth SIAM International Conference on Data Mining (SDM 2008)
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T. Lin, P. Ray, G. K. Sandve, S. Uguroglu, and E. P. Xing, BayCis: a Bayesian hierarchical HMM for cis-regulatory module decoding in metazoan genomes, Proceedings of the Twelfth Annual International Conference on Research in Computational Molecular Biology (RECOMB2008)
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J. Yang, R. Yan, Y. Liu, and E. P. Xing, Harmonium Models for Video Classification, Journal of Statistical Analysis and Data Mining, Vol 1, issue 1, p23-37, 2008
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W. Wu and E. P. Xing, A Survey of cDNA Microarray Normalization and a Comparison by k-NN Classification, in Methods in Microarray Normalization (Ed. S. Phillip), CRC Press. p81-120, 2008
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2007:

M.-F. Balcan, E. Even-Dar, S. Hanneke, M. Kearns, Y. Mansour, J. Wortman, Asymptotic Active Learning, NIPS Workshop on Principles of Learning Problem Design 2007. (NIPS-WPLPD 07)
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B. Zhao and E. P. Xing, HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation, Advances in Neural Information Processing Systems 20 (NIPS2007)
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L. Chang, N. Pollard, T. Michell and E. P. Xing, Feature selection for grasp recognition from optical markers, Proceedings of the 2007 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems, 2007 (IROS2007)
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E. P. Xing and K. Sohn, A Nonparametric Bayesian Approach for Haplotype Reconstruction from Single and Multi-Population Data, CMU-MLD Technical Report 07-107
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K. Sohn and E. P. Xing, Spectrum: Joint Bayesian Inference of Population Structure and Recombination Event, The Fifteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2007)
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S. Hanneke, A Bound on the Label Complexity of Agnostic Active Learning. Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007)
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F. Guo, S. Hanneke, W. Fu and E. P. Xing, Recovering Temporally Rewiring Networks: A model-based approach, Proceedings of the 24th International Conference on Machine Learning (ICML 2007)
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L. Gu, E. P. Xing, and T. Kanade, Learning GMRF Structures for Spatial Priors, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007)
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S. Hanneke, Teaching Dimension and the Complexity of Active Learning, Proceedings of the 20th Annual Conference on Learning Theory (COLT 2007)
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Z. Guo, Z. Zhang, E. P. Xing, C. Faloutsos, Enhanced Max Margin Learning on Multimodal Data Mining in a Multimedia Database, The Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2007)
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Z. Guo, Z. Zhang, E. P. Xing, C. Faloutsos, A Max Margin Framework on Image Annotation and Multimodal Image Retrieval, IEEE International Conference on Multimedia & Expo (ICME 2007)
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E. P. Xing, M. Jordan, and R. Sharan, Bayesian Haplotype Inference via the Dirichlet Process, Journal of Computational Biology, Vol 14, No 3, pp. 267-284, 2007
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E. P. Xing and K. Sohn, Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space, Bayesian Analysis, Vol 2, No 2, 2007
A synopsis of this paper was published in Bayesian Statistics 8, the Proc. Valencia / ISBA 8th World Meeting on Bayesian Statistics
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A. Ahmed and E. P. Xing, On Tight Approximate Inference of Logistic-Normal Admixture Model, Proceedings of the Eleventh International Conference on Artifical Intelligence and Statistics (AISTAT 2007)
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J. Yang, Y. Liu, E. P. Xing and A. Hauptmann, Harmonium-Based Models for Semantic Video Representation and Classification , Proceedings of The Seventh SIAM International Conference on Data Mining (SDM 2007)
Recipient of the BEST PAPER Award
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H. Kamisetty, E. P. Xing, C. J. Langmead, Free Energy Estimates of All-atom Protein Structures Using Generalized Belief Propagation, The Eleventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2007)
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Y. Shi, F. Guo, W. Wu and E. P. Xing, GIMscan: A New Statistical Method for Analyzing Whole-Genome Array CGH Data, The Eleventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2007)
Tech report version here
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2006:

F. Guo, W. Fu, Y. Shi and E. P. Xing, Reverse engineering temporally rewiring gene networks, The NIPS workshop on New Problems and Methods in Computational Biology (NIPS2006)
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F. Li, Y. Yang and E. P. Xing, Inferring regulatory networks using a hierarchical Bayesian graphical Gaussian model, CMU-MLD Technical Report 06-117
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Y. Shi, F. Guo, W. Wu and E. P. Xing, GIMscan: A New Statistical Method for Analyzing Whole-Genome Array CGH Data, CMU-MLD Technical Report 06-115
Conference version here
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E. P. Xing and K. Sohn, A New Nonparametric Bayesian Model for Genetic Inference in Open Ancestral Space, CMU-MLD Technical Report 06-111
Conference version here
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K. Sohn and E. P. Xing, Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space, Advances in Neural Information Processing Systems 19 (NIPS2006)
Technical report version here
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J-Y Pan, A. Balan, E.P. Xing, A. Traina and C. Faloutsos, Automatic Mining of Fruit Fly Embryo Images, The Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2006)
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B. Zhao and E.P Xing, BiTAM: Bilingual Topic AdMixture Models for Word Alignment, The joint conference of the International Committee on Computational Linguistics and the Association for Computational Linguistics (ACL 2006)
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T. Lin, E.W. Myers and E.P. Xing, Interpreting Anonymous DNA Samples From Mass Disasters - probabilistic forensic inference using genetic markers, Bioinformatics 22(14):e298-e306. (special issue for The Fourteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2006)
This work was parallely presented at The Fourteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2006)
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E.P. Xing, K. Sohn, M.I. Jordan and Y.-W. Teh, Bayesian Multi-Population Haplotype Inference via a Hierarchical Dirichlet Process Mixture, Proceedings of the 23rd International Conference on Machine Learning (ICML 2006)
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S. Hanneke, An Analysis of Graph Cut Size for Transductive Learning, Proceedings of the 23rd International Conference on Machine Learning (ICML 2006)
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S. Hanneke and E.P Xing, Discrete Temporal Models of Social Networks, In proceedings of the Workshop on Statistical Network Analysis, the 23rd International Conference on Machine Learning (ICML-SNA 2006)
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F. Guo and E.P Xing, Bayesian Exponential Family Harmoniums, CMU-MLD Technical Report 06-103
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E.M. Airoldi, D.M. Blei, S.E. Fienberg, E.P. Xing, Latent mixed-membership allocation models of relational and multivariate attribute data, Valencia & ISBA Joint World Meeting on Bayesian Statistics (2006)
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E.M Airodi, D.M. Blei, E.P. Xing and S.E. Fienberg, Mixed membership stochastic block models for relational data, with applications to protein-protein interactions, Proceedings of International Biometric Society-ENAR Annual Meetings (2006).
Recipient of the John Van Ryzin Award
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2005:

E.P. Xing, On Topic Evolution. CMU-CALD Technical Report 05-115
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E.P. Xing, Dynamic Nonparametric Bayesian Models and the Birth-Death Process. CMU-CALD Technical Report 05-114
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W. Wu, N. Dave, G.C. Tseng, T. Richards, E.P. Xing, and N. Kaminsky, Comparison of normalization methods for CodeLink Bioarray data. BMC Bioinformatics 2005, 6:309
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F. Li, Y. Yang and E. P. Xing, From Lasso regression to Feature vector machine, Advances in Neural Information Processing Systems 18 (NIPS2005)
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W. Wu, E.P. Xing, C. Myers, I. S. Mian and M. J. Bissell, Evaluation of normalization methods for cDNA microarray data by k-NN classification. BMC Bioinformatics 2005, 6:191
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E. Airoldi, D. Blei, E.P. Xing and S. Fienberg, A Latent Mixed Membership Model for Relational Data. Workshop on Link Discovery: Issues, Approaches and Applications (LinkKDD-2005)
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E.P. Xing, R. Yan and A. G. Hauptmann, Mining Associated Text and Images with Dual-Wing Harmoniums. Uncertainty in Artificial Intelligence, 2005 (UAI2005)
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Y. Liu, E.P. Xing, and J. Carbonell, Predicting Protein Folds with Structural Repeats Using a Chain Graph Model. Proceedings of the 22st International Conference on Machine Learning (ICML2005)
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B. Zhao, E.P Xing, and A. Waibel, Bilingual Word Spectral Clustering for Statistical Machine Translation. ACL-Workshop-WPT, Ann Arbor MI, 2005
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2004:

E.P. Xing, Probabilistic graphical models and algorithms for genomic analysis Ph.D. Thesis, University of California, Berkeley, July 2004
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(C) SAILING Lab, 2008 Copyright of published papers held by publishing bodies in question