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

2012:


Ross E. Curtis, Jing Xiang, Ankur Parikh, Peter Kinnaird and E. P. Xing. Enabling dynamic network analysis through visualization in TVNViewer, BMC Bioinformatics, 2012
S. Williamson, Z. Ghahramani, S. N. MacEachern and E. P. Xing. Restricting exchangeable nonparametric distributions, Manuscript, arXiv:1209.1145
A. Dubey, A. Hefny, S. Williamson and E. P. Xing. A non-parametric mixture model for topic modeling over time, Manuscript, arXiv:1208.4411
S. Lee and E. P. Xing. Efficient Algorithm for Extremely Large Multi-task Regression with Massive Structured Sparsity, Manuscript, arXiv:1208.3014
S. Lee and E. P. Xing. Structured Input-Output Lasso, with Application to eQTL Mapping, and a Thresholding Algorithm for Fast Estimation, Manuscript, arXiv:1205.1989
N. Foti and S. Williamson. Slice sampling normalized kernel-weighted completely random measure mixture models. NIPS 2012.
Q. Ho, J. Yin and E. P. Xing. On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks. NIPS 2012.
J. Zhu, Q. Jiang, M. Sun and E. P. Xing. Monte Carlo Methods for Maximum Margin Supervised Topic Models. NIPS 2012.
K. Fukumasu, K. Eguchi and E. P. Xing. Symmetric Correspondence Topic Models for Multilingual Text Analysis. NIPS 2012.
K. Puniyani and E. P. Xing. Inferring gene interaction networks from ISH images via kernelized graphical models. ECCV 2012.
M. Kolar, J. Sharpnack. Variance Function Estimation in High-dimensions. ICML 2012.
Sivaraman Balakrishnan, Kriti Puniyani, John Lafferty. Sparse additive functional and kernel CCA. ICML 2012.
Yuening Hu, Ke Zhai, Sinead Williamson, and Jordan Boyd-Graber. Modeling Images using Transformed Indian Buffet Processes. ICML 2012.
A. Parikh, L. Song, M. Ishteva, G. Teodoru and E. P. Xing, A Spectral Algorithm for Latent Junction Trees, Proceedings of the 27th International Conference on Conference on Uncertainty in Artificial Intelli- gence (UAI 2012).
J. Zhu, A. Ahmed, and E. P. Xing, MedLDA: Maximum Margin Supervised Topic Models, Journal of Machine Learning Research (to appear), 2012. ( arXiv:0912.5507)
Q. Ho, A. Parikh and E. P. Xing, Multiscale Community Blockmodel for Network Exploration, Journal of American Statistical Association, 2012. [pdf]
K. Sohn, Z. Ghahramani and E. P. Xing, Robust Estimation of Local Genetic Ancestry in Admixed Populations Using a Non-parametric Bayesian Approach, Genetics (112.140228), 2012. [pdf] [software will be available soon]
R.E. Curtis, A. Goyal and E. P. Xing, Enhancing the usability and performance of structured as- sociation mapping algorithms using automation, parallelization, and visualization in the GenAMap software system, BMC Genetics, vol. 13, no. 24, 2012. [pdf] [software]
J. Hu, Y. Liang and E. P. Xing, Nonparametric Decentralized Detection Based on Weighted Count Kernel, Proceedings of the 2012 IEEE International Symposium on Information Theory (ISIT 2012).
J. Yin, X. Chen and E. P. Xing, Group Sparse Additive Models, The 29th International Conference on Machine Learningy (ICML 2012).
M. Kolar and E. P. Xing, Consistent Covariance Selection From Data With Missing Values, The 29th International Conference on Machine Learningy (ICML 2012).
G. Kim, L. Fei-Fei and E. P. Xing, Web Image Prediction Using Multivariate Point Processes, Proceedings of The 18th ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2012). [software and project page]
G. Kim and E. P. Xing, On Multiple Foreground Cosegmentation, Proceedings of 25th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012). [software and project page]
S. Lee and E. P. Xing, Leveraging Input and Output Structures For Joint Mapping of Epistatic and Marginal eQTLs, the Twenties International Conference on Intelligence Systems for Molecular Biology (ISMB 2012). Bioinformatics 2012. [pdf]
Y. Zhang, D.-Y. Yeung and E. P. Xing, Supervised Probabilistic Robust Embedding with Sparse Noise, Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2012).
N. Chen, J. Zhu, and E. P. Xing, Predictive Subspace Learning for Multi-view Data: a Large Margin Approach, IEEE Transaction on Pattern Analysis and Machine Intelligence, 2012. [Supplemental Material]
S. Kim and E. P. Xing, Tree-Guided Group Lasso for Multi-Response Regression with Structured Sparsity, with applications to eQTL Mapping, Annals of Applied Statistics, 2012.
X. Chen, Q. Lin, S. Kim, J. Carbonell and E. P. Xing, Smoothing Proximal Gradient Method for General Structured Sparse Regression, Annals of Applied Statistics, 2012.
J. Eisenstein, D.H. Chau, A. Kittur, and E. P. Xing, TopicViz: Semantic Navigation of Document Collections, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, Work-in-Progress Paper (CHI 2012).
Q. Ho, J. Eisenstein and E. P. Xing, Document Hierarchies from Text and Links, Proceedings of the International World Wide Web Conference (WWW 2012).
R.E. Curtis, J. Yin, P. Kinnaird and E. P. Xing, Finding Genome-Transcriptome-Phenome Association With Structured Association Mapping And Visualization In GenAMap, Pacific Symposium on Biocomputing 2012 (PSB 2012). [software and project page]
R. E. Curtis, A. Goyal, E. P. Xing, Enhancing the usability and performance of structured association mapping algorithms using automation, parallelization, and visualization in the GenAMap software system. BMC Genetics 13(24) doi:10.1186/1471-2156-13-24
R. E. Curtis, J. Yin, P. Kinnaird, E. P. Xing, Finding Genome-Transcriptome-Phenome Association with Structured Association Mapping and Visualization in GenAMap Pacific Symposium on Biocomputing 17:327-338

2011:

R. E. Curtis, P. Kinnaird, E. P. Xing, GenAMap: Visualization Strategies for Structured Association MappingIEEE Symposium on Biological Data Visualization 1:87-95.
X. Chen, Q. Lin, S. Kim, J. Carbonell and E. P. Xing, Smoothing Proximal Gradient Method for General Structured Sparse Learning, Proceedings of the 27th International Conference on Conference on Uncertainty in Artificial Intelli- gence (UAI 2011).
Code: SPG for Uni-response Overlapping group lasso and Graph-guided Fused Lasso
Code: SPG for Multi-task Graph-guided Fused Lasso
J. Zhu and E. P. Xing, Sparse Topical Coding, Proceedings of the 27th International Conference on Conference on Uncertainty in Artificial Intelli- gence (UAI 2011).
G. Kim, E. P. Xing, L. Fei-Fei and T. Kanade, Distributed Cosegmentation via Submodular Optimization on Anisotropic Diffusion, Proceedings of 13th International Conference on Computer Vision (ICCV 2011).
R. E. Curtis, A. Yuen, L. Song, A. Goyal and E. P. Xing, TVNViewer: An interactive visualization tool for exploring networks that change over time or space, Bioinformatics 27(13):1880-1881 (2011).
A. Parikh, W. Wu, R. E. Curtis and E. P. Xing, Reverse Engineering Tree-Evolving Gene Networks Underlying Developing Biological Lineages, the Nineteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2011). Bioinformatics 2011.
S. Shringarpure, D. Won and E. P. Xing, StructHDP: Automatic inference of number of clusters from admixed genotype data, the Nineteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2011). Bioinformatics 2011.
Q. Ho, A. Parikh, L. Song and E. P. Xing, Multiscale Community Blockmodel for Network Exploration, Proceedings of the 14th International Conference on Artifical Intelligence and Statistics (AISTAT 2011). [Supplemental Material]
Q. Ho, L. Song and E. P. Xing, Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks, Proceedings of the 14th International Conference on Artifical Intelligence and Statistics (AISTAT 2011). [Supplemental Material] [Senator Dataset]
A.F.T. Martins, M.A.T. Figueiredo, P.M.Q. Aguiar, N.A. Smith and E. P. Xing, Online Learning of Structured Predictors with Multiple Kernels, Proceedings of the 14th International Conference on Artifical Intelligence and Statistics (AISTAT 2011). [Supplemental Material]
M. Kolar and E. P. Xing, On Time Varying Undirected Graphs, Proceedings of the 14th International Conference on Artifical Intelligence and Statistics (AISTAT 2011). [Supplemental Material]
A. Ahmed, Q. Ho, J. Eisenstein, E. P. Xing, A. Smola and C. H. Teo, Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text, Proceedings of the 14th International Conference on Artifical Intelligence and Statistics (AISTAT 2011). [Supplemental Material]
B. Zhao, L. Fei-Fei and E. P. Xing, Online Detection of Unusual Events in Videos via Dynamic Sparse Coding, Proceeding of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011).
J. Eisenstein, N. Smith and E. P. Xing, Discovering Sociolinguistic Associations with Structured Sparsity, The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011).
A. Ahmed, Q. Ho, J. Eisenstein, E. P. Xing, A. Smola and C. H. Teo, Unified Analysis of Streaming News, Proceedings of the International World Wide Web Conference (WWW 2011).

2010:

S. Lee, J. Zhu, and E. P. Xing, Detecting eQTLs using Adaptive Multi-task Lasso, Advances in Neural Information Processing Systems 24 (NIPS 2010).
J. Zhu, J. Li, L. Fei-Fei, and E. P. Xing, Large Margin Learning of Upstream Scene Understanding Models, Advances in Neural Information Processing Systems 24 (NIPS 2010).
J. Li, H. Su, E. P. Xing, and L. Fei-Fei, Object Bank: A High-Level Image Representation for Scene Classification and Semantic Feature Sparsification, Advances in Neural Information Processing Systems 24 (NIPS 2010).
A. Ahmed and E. P. Xing, Staying Informed: Multi-view Topical Analysis of Ideological Perspective, 2010 Conference on Empirical Methods on Natural Language Processing (EMNLP 2010).
J. Eisenstein, B. Oâ¿¿Connor, N. A. Smith, and E. P. Xing, A Latent Variable Model for Geographic Lexical Variation, 2010 Conference on Empirical Methods on Natural Language Processing (EMNLP 2010).
A. F. T. Martins, N. A. Smith, E. P. Xing, M. Figueiredo, and P. Aguiar, A Latent Variable Model for Geographic Lexical Variation, 2010 Conference on Empirical Methods on Natural Language Processing (EMNLP 2010).
S. Hanneke, W. Fu and E. P. Xing, Discrete Temporal Models of Social Networks, Electronic Journal of Statistics Vol. 4 (2010) 585-605. (arXiv:0908.1258, communicated August 2009.)
A. Ahmed and E. P. Xing, Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream, Proceedings of the 26th International Conference on Conference on Uncertainty in Artificial Intelli- gence (UAI 2010).
B. Zhao, L. Fei-Fei and E. P. Xing, Image Segmentation with Topic Random Fields, Proceeding of the 12th European Conference of Computer Vision (ECCV 2010).
G. Kim, E. P. Xing, and A. Torralba, Modeling and Analysis of Dynamic Behaviors of Web Image Collections, Proceeding of the 12th European Conference of Computer Vision (ECCV 2010).
J. Zhu, N. Lao and E. P. Xing, Grafting-Light: Fast, Incremental Feature Selection and Structure Learning of Markov Random Fields, Proceedings of The 16th ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2010).
X. Chen, Q. Lin, S. Kim, J. Peÿ±a, J. G. Carbonell and E. P. Xing, An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity, Manuscript, arXiv:1005.4717, communicated May 2010.
X. Chen, S. Kim, Q. Lin, J. G. Carbonell and E. P. Xing, Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso,Manuscript, arXiv:1005.3579, communicated May 2010.
S. Kim and E. P. Xing, Exploiting Genome Structure in Association Analysis, Journal of Computational Biology (to appear) 2010.
M. Kolar, A. Parikh and E. P. Xing, On Sparse Nonparametric Conditional Covariance Selection, The 27th International Conference on Machine Learningy (ICML 2010).
S. Kim and E. P. Xing, Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity, The 27th International Conference on Machine Learningy (ICML 2010).
J. Zhu and E. P. Xing, Conditional Topic Random Fields, The 27th International Conference on Machine Learningy (ICML 2010).
K. Puniyani, S. Kim and E. P. Xing, Multi-Population GWA Mapping via Multi-Task Regularized Regression, the Eighteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2010). Bioinformatics 2010 26(12):i208-i216.
K. Puniyani, C. Faloutsos and E. P. Xing, SPEX2 : Automated Concise Extraction of Spatial Gene Expression Patterns from Fly Embryo ISH Images, the Eighteenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2010). Bioinformatics 2010 26(12):i47-i56.
M. Kolar and E. P. Xing, Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit, Proceedings of the 13th International Conference on Artifical Intelligence and Statistics (AISTAT 2010). [Supplemental Material]
S. Lee, E. P. Xing and M. Brudno, MoGUL: Detecting Common Insertions and Deletions in a Population, Proceedings of the Fourteenth Annual International Conference on Research in Computational Molecular Biology (RECOMB2010). [software]

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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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).
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
L. Song, M. Kolar and E. P. Xing, Time-Varying Dynamic Bayesian Networks, Proceedings of the 23rd Neural Information Processing Systems, (NIPS 2009).
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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).
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
S. Kim and E. P. Xing, Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity Manuscript, arXiv:0909.1373, communicated September 2009.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
S. Hanneke, W. Fu and E. P. Xing, Discrete Temporal Models of Social Networks, Manuscript, arXiv:0908.1258, communicated August 2009.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
M. Kolar and E. P. Xing, Sparsistent Estimation of Time-Varying Discrete Markov Random Fields, Manuscript, arXiv:0907.2337, communicated July 2009.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
J. Zhu and E. P. Xing, Maximum Entropy Discrimination Markov Networks, Manuscript, arXiv:0901.2730, communicated January 2009.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Seyoung Kim and Eric P. Xing, Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network, PLoS Genetics (to appear).
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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).
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Steve Hanneke, Theoretical Foundations of Active Learning Ph.D. Thesis, Carnegie Mellon University, Pittsburgh, April 2009
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Steve Hanneke and Eric P. Xing, Network Completion and Survey Sampling, Proceedings of the 12th International Conference on Artifical Intelligence and Statistics (AISTAT 2009)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Andre Martins, Mario Figueiredo, Pedro Aguiar, Noah A. Smith, and Eric P. Xing, Nonextensive Entropic Kernels, Journal of Machine Learning Research, 2009
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Jun Zhu and Eric P. Xing, Maximum Entropy Discrimination Markov Networks, arXiv, communicated January 2009
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)

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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Wenjie Fu, Le Song, and Eric Xing, A State-Space Mixed Membership Blockmodel for Dynamic Network Tomography , arXiv, communicated December 2008
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Mladen Kolar, Eric Xing, Improved Estimation of High-dimensional Ising Models, arXiv, communicated November 2008
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
Jun Zhu, Eric Xing, Bo Zhang, Partially Observed Maximum Entropy Discrimination Markov Networks., Proceeding of the 22nd Neural Information Processing Systems (NIPS 2008)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide) | Pubmed
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.
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)

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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
B. Zhao and E. P. Xing, HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation, Advances in Neural Information Processing Systems 20 (NIPS2007)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
S. Hanneke, Teaching Dimension and the Complexity of Active Learning, Proceedings of the 20th Annual Conference on Learning Theory (COLT 2007)
PDF | Presentation | Project URL | Publication URL | Bibtex (show/hide)
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