Eric Xing's Publications List

PUBLICATION

Year of Publication :

[2015] [2014] [2013] [2012] [2011] [2010] [2009] [2008] [2007] [2006] [2005] [2004] [2003] [2002] [2001] [Pre-2000]

Type of Publication :

[Show all] [Theses] [Book & book chapters] [Journal] [Conference] [Tech reports] [Workshop] [arXiv manuscripts]

Broad Content :

[Show all] [Machine Learning] [Parallel ML Systems] [Social Network and Media] [Computational Biology] [IR, NLP & Vision]

Research Area :

[Statistical Genetics] [Evolutionary & Regulatory genomics] [Systems Biology] [Structural Biology]

[Prababilistic models] [High-Dim inference & structural sparsity] [Graphs & networks] [Joint max-entropy/max-margin learning]
[Bayesian nonparametrics] [Topic & latent space models] [Learning metrics, kernels, and embeddings] [Probablistic Inference] [Optimization] [Big Learning] [Natural Language Processing] [Computer Vision] [Miscellaneous]

Latest Manuscripts:

Xun Zheng, Jin Kyu Kim, Qirong Ho and E. P. Xing, Model-Parallel Inference for Big Topic Models, Manuscript, arXiv:1411.2305, communicated 10 Nov 2014.

S. Lee and E. P. Xing, Screening Rules for Overlapping Group Lasso, Manuscript, arXiv:1410.6880, communicated 25 Oct 2014).

Pengtao Xie, Jin Kyu Kim and E. P. Xing, Large Scale Distributed Multiclass Logistic Regression, Manuscript, arXiv:1409.5705, communicated 19 Sep 2014.

Pengtao Xie and E. P. Xing, CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph, Manuscript, arXiv:1409.5021, communicated 17 Sep 2014.

Q. Ho, R. Yan, R. Raina and E. P. Xing, Understanding the Interaction between Interests, Conversations and Friendships in Facebook, Manuscript, arXiv:1211.0028, communicated 31 Oct 2012.

S. Lee and E. P. Xing, Efficient Algorithm for Extremely Large Multi-task Regression with Massive Structured Sparsity, Manuscript, arXiv:1208.3014, communicated 15 Aug 2012).

Published:

2015

E. P. Xing, Q. Ho, W. Dai, J. Kim, J. Wei, S. Lee, X. Zheng, P. Xie, A. Kumar, and Y. Yu, Petuum: A new Platform for Distributed Machine Learning on Big Data, IEEE Transactions on Big Data, in press, 2015. ( arXiv:1312.7651, communicated 30 Dec 2013.)

Bin Zhao and E. P. Xing, Sparse Output Coding for Scalable Visual Recognition, International Journal of Computer Vision, in press, 2015.

W. Wang, Y. Liang, Lixin Shen, and E. P. Xing, Nonparametric Decentralized Detection and Sparse Sensor Selection via Weighted Kernel, IEEE Transactions on Signal Processing, in press, 2015.

L. Song, H. Liu, A. Parikh, and E. P. Xing, Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning, Journal of Machine Learning Research, in press, 2015. ( arXiv:1401.3940, communicated 16 Jan 2014.)

A. Martins, M. Figueiredo, P. Aguiar, N.A. Smith and E. P. Xing, AD3: Alternating Directions Dual Decomposition for MAP Inference in Graphical Models , Journal of Machine Learning Research, 16(Mar): 495-545, 2015. ( arXiv:1212.6550, communicated 28 Dec 2012.)

J. Wei, W. Dai, A. Qiao, H. Cui, Q. Ho, G. R. Ganger, P. B. Gibbons, G. A. Gibson, and E.P. Xing, Managed Communication and Consistency for Fast Data-Parallel Iterative Analytics, ACM Symposium on Cloud Computing, 2015 (SoCC 2015). (Recipient of the Best Paper Award)

E. P. Xing, Q. Ho, W. Dai, J. Kim, J. Wei, S. Lee, X. Zheng, P. Xie, A. Kumar, and Y. Yu, Petuum: A new Platform for Distributed Machine Learning on Big Data, Proceedings of The 21st ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2015).

P. Xie, Y. Deng and E. P. Xing, Diversifying Restricted Boltzmann Machine for Document Modeling, Proceedings of The 21st ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2015).

X. Zheng, Y. Yu and E. P. Xing, Linear Time Samplers for Supervised Topic Models using Compositional Proposals, Proceedings of The 21st ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2015).

H. Zhang, G. Kim and E. P. Xing, Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data, Proceedings of The 21st ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2015).

X. Chang, Y. Yang, A. G. Hauptmann, E. P. Xing, Y. Yu and E.P. Xing, Semantic Concept Discovery for Large- Scale Zero-Shot Event Detection, The 24th International Joint Conference on Artificial Intelligence. (IJCAI 2015).

M. Sachan, E. Hovy and E.P. Xing, An Active Learning approach to Coreference Resolution, The 24th International Joint Conference on Artificial Intelligence. (IJCAI 2015).

M. Sachan, A. Dubey, M.Richardson and E.P. Xing, Learning Answer-Entailing Structures for Machine Comprehension , 53rd Annual Meeting of the Association for Computational Linguistics. (ACL 2015). (Recipient of an Honorable Mentioning)

Z. Hu, P. Huang, Y. Deng, Y. Gao and E. P. Xing, Entity Hierarchy Embedding, 53rd Annual Meeting of the Association for Computational Linguistics. (ACL 2015).

X. Chang, Y. Yu and E. P. Xing, Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM, The 32th International Conference on Machine Learning. (ICML 2015).

Z. Hu, Q. Ho, A. Dubey and E. P. Xing, Large-scale Distributed Dependent Nonparametric Trees, The 32th International Conference on Machine Learning. (ICML 2015).

Z. Hu, J. Yao, B. Cui and E. P. Xing, Community Level Diffusion Extraction, Proceedings of the 2015 ACM SIGMOD international conference on Management of data. (SIGMOD 2015).

P. Xie, D. Yang and E. P. Xing, Incorporating Word Correlation Knowledge into Topic Modeling, Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL 2015).

J. Yuan, F. Gao, Q. Ho, W. Dai, J. Wei, X. Zheng, E. P. Xing, T. Liu and W. Ma, LightLDA: Big Topic Models on Modest Compute Clusters, Proceedings of the 24th international conference on World Wide Web. (WWW 2015). ( arXiv:1412.1576, communicated 4 Dec 2014.)

Y. Yu, X. Zheng, M. Marchetti-Bowick and E. P. Xing, Minimizing Nonconvex Non-Separable Functions, Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics. (AISTATS 2015).

J. Oliva, W. Neiswanger, B. Poczos, E. P. Xing and J. Schneider, Fast Function to Function Regression, Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics. (AISTATS 2015).

P. Xie and E. P. Xing, Integrating Image Clustering and Codebook Learning, Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015. (AAAI 2015).

P. Xie, Y. Pei, Y. Xie, and E. P. Xing, Mining User Interests from Personal Photos, Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015. (AAAI 2015).

W. Dai, A. Kumar, J. Wei. Q. Ho, G. Gibson and E. P. Xing, High-Performance Distributed ML at Scale through Parameter Server Consistency Models, Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015. (AAAI 2015). ( arXiv:1312.7869, communicated 30 Dec 2013.) [Supplemental Material]

S. Lee, A. Lozano, P. Kambadur and E. P. Xing, An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations, 19th International Conference on Research in Computational Molecular Biology. (RECOMB 2015).

2014

W. Wang, Y. Liang and E. P. Xing, Sharp Threshold for Multivariate Multi-Response Linear Regression via Block Regularized Lasso, IEEE Transactions on Information Theory, in press, 2014.

J. Eisenstein, B. O’Connor, N. A. Smith, and E. P. Xing, Diffusion of Lexical Change in Social Media, PLoS One, volume 9, Issue 11, e113114, 2014. ( arXiv:1210.5268, communicated 18 Oct 2012.) [pdf preprint]

S. Lee, J. K. Kim, X. Zheng, Q. Ho, G. A. Gibson, and E. P. Xing, On Model Parallelization and Scheduling Strategies for Distributed Machine Learning, Advances in Neural Information Processing Systems 28 (eds. Corinna Cortes and Neil Lawrence), MIT Press, 2014. (NIPS 2014). ( arXiv:1312.5766, communicated 19 Dec 2013.) [Supplemental Material]

A. Dubey, Q. Ho, S.Williamson, and E. P. Xing, Dependent Nonparametric Trees for Dynamic Hierarchical Clustering, Advances in Neural Information Processing Systems 28 (eds. Corinna Cortes and Neil Lawrence), MIT Press, 2014. (NIPS 2014). [Supplemental Material]

A. P. Parikh, A. Saluja, C. Dyer and E. P. Xing, Language Modeling with Power Low Rank Ensembles, Proceeding of the 2014 Conference on Empirical Methods on Natural Language Processing. (EMNLP 2014). (Recipient of the runner-up for BEST PAPER Award) ( arXiv:1312.7077, communicated 26 Dec 2013.) [Supplemental Material]

W. Neiswanger, C. Wang and E. P. Xing, Asymptotically Exact, Embarrassingly Parallel MCMC, Proceedings of the 30th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI 2014). ( arXiv:1311.4780, communicated 19 Nov 2013.)

W. Neiswanger, C. Wang, Q. Ho and E. P. Xing, Modeling Citation Networks using Latent Random Offsets, Proceedings of the 30th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI 2014).

A. Dubey, S.Williamson and E. P. Xing, Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models, Proceedings of the 30th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI 2014). [Supplemental Material]

H. Cui, A. Tumanov, J. Wei, L. Xu, W. Dai, J. Haber-Kucharsky, Q. Ho, G. R. Ganger, P. B. Gibbons, G. A. Gibson, and E.P. Xing, Exploiting Iterative-ness for Parallel ML Computations, ACM Symposium on Cloud Computing, 2014 (SoCC 2014).

H. Cui, J. Cipar, Q. Ho, J-K Kim, S. Lee, A. Kumar, J. Wei, W. Dai, G. R. Ganger, P. B. Gibbons, G. A. Gibson, and E. P. Xing, Exploiting Bounded Staleness to Speed up Big Data Analytics, USENIX Annual Technical Conference , June 19-20, 2014. Philadelphia, PA (ATC 2014).

A. Parikh, R. Curtis, I. Kuhn, S. Becker, M. Bissell, E. P. Xing and W. Wu, Network Analysis of Breast Cancer Progression and Reversal Using a Tree-evolving Network Algorithm, PLoS Computational Biology, Volume 10, Issue 7, e1003713, 2014. [pdf preprint].

E. P. Xing, R. Curtis, G. Schoenherr, S. Lee, J. Yin, K. Puniyani, W. Wu, P. Kinnaird, GWAS in a Box: Statistical and Visual Analytics of Structured Associations via GenAMap, PLoS One, Volume 9, Issue 6, e97524, 2014. [pdf preprint].

S. Shringarpure and E. P. Xing, Effects of Sample Selection Bias on the Accuracy of Population Structure and Ancestry Inference, Genes, Genomes, Genetics, vol. 4 no. 5 901-911, 2014, [pdf preprint].

D. Yogatama, C. Wang, B.R. Routledge, N.A. Smith and E. P. Xing, Dynamic Language Models for Streaming Text, Transactions of the Association for Computational Linguistics 2:181-192, 2014 (TACL 2014).

A. Parikh, S. Cohen and E. P. Xing, Spectral Unsupervised Parsing with Additive Tree Metrics, The 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014).

G. Kim and E. P. Xing, Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos, Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014).

G. Kim, L. Sigal and E. P. Xing, Jointly Summarizing Large-Scale Web Images and Videos for the Storyline Reconstruction, Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014).

B. Zhao and E. P. Xing, Quasi Real-Time Summarization for Consumer Videos, Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014).

B. Zhao and E. P. Xing, Hierarchical Feature Hashing for Fast Dimensionality Reduction, Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014).

M. Kolar, H. Liu and E. P. Xing, Graph Estimation From Multi-attribute Data , Journal of Machine Learning Research, 15:1713-1750, 2014. ( arXiv:1210.7665, communicated 29 Oct 2012.)

J. Zhu, N. Chen, and E. P. Xing, Bayesian Inference with Posterior Regularization, and applications to Infinite Latent SVMs , Journal of Machine Learning Research, 15:1799-1847, 2014. ( arXiv:1210.1766)

A. Kumar, A. Beutel, Q. Ho and E. P. Xing, Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data, Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014).

J. B. Oliva, W. Neiswanger, B. Poczos, J. Schneider and E. P. Xing, Fast Distribution To Real Regression, Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014).

W. Neiswanger, F. Wood and E. P. Xing, The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling, Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014).

A. Beutel, A. Kumar, E. E. Papalexakis, P. P. Talukdar, C. Faloutsos and E. P. Xing, FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop, Proceedings of The 14th SIAM International Conference on Data Mining (SDM 2014).

G. Kim and E. P. Xing, Visualizing Brand Associations from Web Community Photos, Proceedings of The 7th ACM International Conference on Web Search and Data Mining (WSDM 2014). [software and project page]

M. Sachan, A. Dubey, S. Srivastava, E. P. Xing and Eduard Hovy, Spatial Compactness meets Topical Consistency: Jointly modeling Links and Content for Community Detection , Proceedings of The 7th ACM International Conference on Web Search and Data Mining (WSDM 2014).

A. P. Parikh, W. Wu, and E. P. Xing, Robust Reverse Engineering of Dynamic Gene Networks under Sample Heterogeneity, Pacific Symposium on Biocomputing 2014 (PSB 2014).

2013

Q. Ho, J. Cipar, H. Cui, J.-K. Kim, S. Lee, P. B. Gibbons, G. Gibson, G. R. Ganger and E. P. Xing, More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server, Advances in Neural Information Processing Systems 27 (NIPS 2013). [Supplemental Material]

S. Williamson, S. N. MacEachern and E. P. Xing, Restricting exchangeable nonparametric distributions, Advances in Neural Information Processing Systems 27 (NIPS 2013). [Supplemental Material] ( arXiv:1209.1145)

J. Yin, Q. Ho and E. P. Xing, A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks, Advances in Neural Information Processing Systems 27 (NIPS 2013). [Supplemental Material]

C. Wang, X. Chen, A. Smola and E. P. Xing, Variance Reduction for Stochastic Gradient Optimization, Advances in Neural Information Processing Systems 27 (NIPS 2013). [Supplemental Material]

G. Kim and E. P. Xing, Discovering Pictorial Brand Associations from Large-Scale Online Image Data, Proceedings of The 7th ACM International Conference on Web Search and Data Mining (lsviscom2013). [software and project page] (Recipient of the BEST PAPER Award)

K Puniyani and E. P. Xing, GINI:From ISH images to Gene Interaction Networks, PLoS Computational Biology, 9(10): e1003227, 2013 [pdf preprint].

M. Yamada, W. Jitkrittum, L. Sigal, E. P. Xing and M. Sugiyama, High-Dimensional Feature Selection by Feature-Wise Non-Linear Lasso, Neural Computation, Vol. 26, No. 1, Pages 185-20, 2013. [pdf preprint] ( arXiv:1202.0515)

P. Xie and E. P. Xing, Integrating Document Clustering and Topic Modeling, Proceedings of the 29th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI 2013).

T. Bahadori, Y. Liu and E. P. Xing, Fast Structure Learning in Generalized Stochastic Processes with Latent Factors, Proceedings of The 19th ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2013).

P. Xie and E. P. Xing, Multi-Modal Distance Metric Learning, 23rd International Joint Conference on Artificial Intelligence (IJCAL 2013).

A. Ahmed and E. P. Xing, Scalable Dynamic Nonparametric Bayesian Models of Content and Users, 23rd International Joint Conference on Artificial Intelligence (IJCAL 2013). [Invited to Sister Conference Best Papers Track, based on KDD12 best Ph.D. dissertation award]

J. Cipar, Q. Ho, J.-K. Kim, S. Lee, G. R. Ganger, G. Gibson, K. Keeton and E. P. Xing, Solving the straggler problem with bounded staleness, The 14th Workshop on Hot Topics in Operating Systems (HotOS XIV).

R.E. Curtis, S. Kim, J. L. Woolford, W. Xu and E. P. Xing, Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules, BMC Genomics 2013, vol. 14, no. 196, 2013. [pdf]

G. Kim and E. P. Xing, Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines, Proceedings of 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2013). [software and project page][Supplemental Material]

B. Zhao and E. P. Xing, Sparse Output Coding for Large-scale Visual Recognition, Proceedings of 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2013).

W. Wang, Y. Liang and E. P. Xing, Block Regularized Lasso for Multivariate Multi-Response Linear Regression, Proceedings of the 16th International Conference on Artifical Intelligence and Statistics (AISTAT 2013).

M. Kolar, H. Liu and E. P. Xing, Markov Network Estimation From Multi-attribute Data, The 30th International Conference on Machine Learningy (ICML 2013).

L. Song, M. Ishteva, A.P. Parikh, H. Park and E. P. Xing, Hierarchical Tensor Decomposition for Latent Tree Graphical Models, The 30th International Conference on Machine Learningy (ICML 2013).

R. Ranganath, C. Wang, D. Blei and E. P. Xing, An adaptive learning rate for stochastic variational inference, The 30th International Conference on Machine Learningy (ICML 2013).

A. Dubey, S. Williamson and E. P. Xing, Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models, The 30th International Conference on Machine Learningy (ICML 2013). [Supplemental Material]

K Puniyani and E. P. Xing, NP-MuScL: Unsupervised global prediction of interaction networks from multiple data sources, Proceedings of the Seventeenth Annual International Conference on Research in Computational Molecular Biology (RECOMB2013). [software]

A. Dubey, S. Williamson and E. P. Xing, A nonparametric mixture model for topic modeling over time, Proceedings of The Thirteenth SIAM International Conference on Data Mining (SDM2013). (arXiv:1208.4411, communicated 22 Aug 2012.)

G. Kim and E. P. Xing, Time-Sensitive Web Image Ranking and Retrieval via Dynamic Multi-Task Regression, Proceedings of The 6th ACM International Conference on Web Search and Data Mining (WSDM 2013). [software and project page]

2012

M. Kolar and E. P. Xing, Estimating Networks With Jumps, Electronic Journal of Statistics Vol. 6 (2012) 2069-2106. (arXiv:1012.3795, communicated 17 Dec 2010.)

Q. Ho, J. Yin and E. P. Xing, On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks, Advances in Neural Information Processing Systems 26 (NIPS 2012). [Supplemental Material] [software]

Q. Jiang, J. Zhu, M. Sun and E. P. Xing, Monte Carlo Methods for Maximum Margin Supervised Topic Models, Advances in Neural Information Processing Systems 26 (NIPS 2012). [Supplemental Material] [software]

K. Fukumasu, K. Eguchi and E. P. Xing, Symmetric Correspondence Topic Models for Multilingual Text Analysis, Advances in Neural Information Processing Systems 26 (NIPS 2012).

K. Puniyani and E. P. Xing, Inferring gene interaction networks from ISH images via kernelized graphical models, Proceeding of the 13th European Conference of Computer Vision (ECCV 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 Intelligence (UAI 2012). [Supplemental Material]

J. Zhu, A. Ahmed, and E. P. Xing, MedLDA: Maximum Margin Supervised Topic Models, Journal of Machine Learning Research 13 (2012) 2237-2278. ( arXiv:0912.5507)

Q. Ho, A. Parikh and E. P. Xing, A Multiscale Community Blockmodel for Network Exploration, Journal of American Statistical Association, volume 107, issue 499, 916-934, 2012. [pdf preprint]

K. Sohn, Z. Ghahramani and E. P. Xing, Robust Estimation of Local Genetic Ancestry in Admixed Populations Using a Non-parametric Bayesian Approach, Genetics, vol 191, no. 4, 2012. [pdf preprint] [Supplemental Material] [software]

R.E. Curtis, J. Xiang, A. Parikh, P. Kinnaird and E. P. Xing, Enabling dynamic network analysis through visualization in TVNViewer, BMC Bioinformatics, vol. 13, no. 204, 2012. [pdf] [software]

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). [Supplemental Material] [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) 28 (12): i137-i146. [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, Volume 6, Number 3 (2012), 1095-1117. [pdf]

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, Volume 6, Number 2 (2012), 719-752. [pdf]

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]

2011

L. Song, A. Parikh and, and E. P. Xing, Kernel Embeddings of Latent Tree Graphical Models, Advances in Neural Information Processing Systems 25 (NIPS 2011). [Supplemental Material]

J. Zhu, N. Chen and E. P. Xing, Infinite Latent SVM for Classification and Multi-task Learning, Advances in Neural Information Processing Systems 25 (NIPS 2011).

B. Zhao, L. Fei-Fei and E. P. Xing, Large-Scale Category Structure Aware Image Categorization, Advances in Neural Information Processing Systems 25 (NIPS 2011).

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).

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).[Supplemental Material] [software and project page]

R.E. Curtis, P. Kinnaird and E. P. Xing, GenAMap: Visualization Strategies for Structured Association Mapping, 1st IEEE Symposium on Biological Data Visualization, 2011. [software]

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 2011. [software]

J. Zhu, N. Lao, N. Chen and E. P. Xing, Conditional Topical Coding: an Efficient Topic Model Conditioned on Rich Features, Proceedings of The 17th ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2011).

J. Zhu, N. Chen and E. P. Xing, Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines, The 28th International Conference on Machine Learningy (ICML 2011).

A.F.T. Martins, M.A.T. Figueiredo, P.M.Q. Aguiar, N.A. Smith and E. P. Xing, An Augmented Lagrangian Approach to Constrained MAP Inference, The 28th International Conference on Machine Learningy (ICML 2011).

A. Parikh, L. Song and E. P. Xing, A Spectral Algorithm for Latent Tree Graphical Models, The 28th International Conference on Machine Learningy (ICML 2011).

H. Kamisetty, E. P. Xing, C. J. Langmead, Approximating Correlated Equilibria using Relaxations on the Marginal Polytope, The 28th International Conference on Machine Learningy (ICML 2011).

J. Eisenstein, A. Ahmed and E. P. Xing, Sparse Additive Generative Models of Text, The 28th International Conference on Machine Learningy (ICML 2011).

A. Parikh*, W. Wu* (equal contributing 1st author), R. 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, Volume 27, Issue 13Pp. i196-i204. [pdf] [software] (Recipient of the BEST PAPER Award)

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, Volume 27, Issue 13Pp. i324-i332. [pdf] [software]

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]

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, C. H. Teo, J. Eisenstein, A. Smola and E. P. Xing, 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). Watch a movie of our detection demo on youtube!

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).

S. Kim and E. P. Xing, Exploiting Genome Structure in Association Analysis, Journal of Computational Biology, Volume: 18,Pages: 1-16, 2011. [Journal Link]

2010

S. Lee, J. Zhu, and E. P. Xing, Adaptive Multi-Task Lasso: with application to eQTL detection, Advances in Neural Information Processing Systems 24 (NIPS 2010).

N. Chen, J. Zhu, and E. P. Xing, Predictive Subspace Learning for Multi-view Data: a Large Margin Approach, 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).

Q. Ho, A.P. Parikh, L. Song and E. P. Xing, Infinite Hierarchical MMSB Model for Nested Communities/Groups in Social Networks, Manuscript, arXiv:1010.1868, communicated Oct 2010.

A.F.T. Martins, M.A.T. Figueiredo, P.M.Q. Aguiar, N.A. Smith and E. P. Xing, Online Multiple Kernel Learning for Structured Prediction, Manuscript, arXiv:1005.2770, communicated Oct 2010.

A. Ahmed and E. P. Xing, Staying Informed: Supervised and Semi-Supervised Multi-view Topical Analysis of Ideological Perspective, 2010 Conference on Empirical Methods on Natural Language Processing (EMNLP 2010).

J. Eisenstein, B. O'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, Turbo Parsers: Dependency Parsing by Approximate Variational Inference, 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. Pena, J. G. Carbonell and E. P. Xing, An Efficient Proximal Gradient Method for General Structured Sparse Learning, 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.

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

J. Zhu, A. Ahmed, and E. P. Xing, MedLDA: A General Framework of Maximum Margin Supervised Topic Models, Manuscript, arXiv:0912.5507, communicated Dec 2009.

E.P. Xing, W. Fu, and L. Song, A State-Space Mixed Membership Blockmodel for Dynamic Network Tomography, Annals of Applied Statistics, Vol. 4, No. 2, 535 - 566, 2010. (earlier version appeared in arXiv:0901.0135)

M. Kolar, L. Song, A. Ahmed, and E. P. Xing, Estimating Time-Varying Networks , Annals of Applied Statistics, Vol. 4, No. 1, 94 - 123, 2010. (earlier version appeared in arXiv:0812.5087)

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). [appendix available soon]

L. Song, M. Kolar and E. P. Xing, Time-Varying Dynamic Bayesian Networks, Proceeding of the 23rd Neural Information Processing Systems, (NIPS 2009). [appendix available soon]

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.

M. Kolar and E. P. Xing, Sparsistent Estimation of Time-Varying Discrete Markov Random Fields, Manuscript, arXiv:0907.2337, communicated July 2009.

J. Zhu and E. P. Xing, Maximum Entropy Discrimination Markov Networks, (arXiv:0901.2730) Journal of Machine Learning Research, 10(Nov):2531-2569, 2009.

S. Kim and E. P. Xing, Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network, PLoS Genetics 5(8): e1000587. [pdf] [software]

A. Ahmed and E. P. Xing, TESLA: Recovering Time-Varying Networks of Dependencies in Social and Biological Studies, Proc. Natl. Acad. Sci. USA, vol. 106, no. 29, 11878-11883. [pdf] [supplemental material] [software]

J. Zhu, A. Ahmed and E. P. Xing, MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification, The 26th International Conference on Machine Learningy (ICML 2009).

J. Zhu and E. P. Xing, On Primal and Dual Sparsity of Markov Networks, The 26th International Conference on Machine Learningy (ICML 2009).

W. Fu, L. Song and E. P. Xing, Dynamic Mixed Membership Block Model for Evolving Networks, The 26th International Conference on Machine Learningy (ICML 2009).

A. Martins, N. Smith and E. P. Xing, Polyhedral Outer Approximations with Application to Natural Language Parsing, The 26th International Conference on Machine Learningy (ICML 2009).

A. Martins, N. Smith and E. P. Xing, Concise Integer Linear Programming Formulations for Dependency Parsing, The 47th Annual Meeting of the Association for Computational Linguistics (ACL 2009). (Recipient of the BEST PAPER Award)

J. Zhu, E.P. Xing and B. Zhang, Primal Sparse Max-Margin Markov Networks, The 15th ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2009).

A. Ahmed, E.P. Xing, W. Cohen, and R. Murphy, Structured Correspondence Topic Models for Mining Captioned Figures in Biological Literature, The 15th ACM SIGKDD Conference on knowledge Discovery and Data Mining (KDD 2009).

S. Kim, K. Sohn and E. P. Xing, A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network, The Seventeenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2009). Bioinformatics 2009 25(12):i204-i212.

L. Song, M. Kolar and E. P. Xing, KELLER: Estimating Time-Evolving Interactions Between Genes, The Seventeenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2009). Bioinformatics 2009 25(12):i128-i136. [software]

W. Fu, P. Ray and E. P. Xing, DISCOVER: A feature-based discriminative method for motif search in complex genomes, The Seventeenth International Conference on Intelligence Systems for Molecular Biology (ISMB 2009). Bioinformatics 2009 25(12):i321-i329.[software]

S. Shringarpure and E. P. Xing, mStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations, Genetics, Vol 182, issue 2, 2009. [pdf] [software]

J. A. Howrylak, T. Dolinay, L. Lucht, Z. Wang, D. C. Christiani, J. M. Sethi1, E. P. Xing, M. P. Donahoe and A. M. K. Choi, Discovery of the gene signature for acute lung injury in patients with sepsis, Physiol. Genomics 37: 133-139, 2009.

S. Hanneke and E. P. Xing, Network Completion and Survey Sampling, Proceedings of the 12th International Conference on Artifical Intelligence and Statistics (AISTAT 2009)

K. Sohn and E. P. Xing, A Hierarchical Dirichlet Process Mixture Model For Haplotype Reconstruction From Multi-Population Data, Annals of Applied Statistics, Vol. 3, no. 2, 791-821, 2009. [pdf] [software]

A. Martins, N. A. Smith, E. P. Xing, M. Figueiredo, and P. Aguiar, Nonextensive Information Theoretic Kernels on Measures, Journal of Machine Learning Research, 2009, Vol 10, pp935-975.

2008

A. Ahmed, L. Song, and E. P. Xing, Time-Varying Networks: Recovering Temporally Rewiring Genetic Networks During the Life Cycle of Drosophila melanogaster, Manuscript, arXiv:0901.0138.

W. Fu, L. Song, and E. P. Xing, A State-Space Mixed Membership Blockmodel for Dynamic Network Tomography, Manuscript, arXiv:0901.0135.

M. Kolar, L. Song, A. Ahmed, and E. P. Xing, Estimating Time-Varying Networks , Manuscript, arXiv:0812.5087.

S. Kim, K. Sohn, and E. P. Xing, A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network , Manuscript, arXiv:0811.2026.

M. Kolar and E. P. Xing, Improved Estimation of High-dimensional Ising Models , Manuscript, arXiv:0811.1239.

J. Zhu, E. P. Xing, and B. Zhang, Partially Observed Maximum Entropy Discrimination Markov Networks, Proceeding of the 22nd Neural Information Processing Systems, (NIPS 2008).

E. Airoldi, D. Blei, S. Fienberg, and E. P. Xing, Mixed Membership Stochastic Blockmodel, Journal of Machine Learning Research, 9(Sep):1981--2014, 2008.
A shorter version of this paper appears in Proceeding of the 22nd Neural Information Processing Systems, (NIPS 2008).

A. F.T. Martins, D. Das, N. A. Smith, and E. P. Xing, Stacking Dependency Parser, Proceedings of Conference on Empirical Methods in Natural Language Processing, (EMNLP 2008).

A. Ahmed, K. Yu, W. Xu, Y. Gong, and E. P. 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).

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 2008).

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).

S. Kim and E. P. Xing, Structured Feature Selection in High-Dimensional Space via Block Regularized Regression, Proceedings of the 24th International Conference on Conference on Uncertainty in Artificial Intelligence, (UAI 2008).

J. Zhu, E. P. Xing, B. Zhang, Laplace Maximum Margin Markov Networks , Proceedings of the 25th International Conference on Machine Learning (ICML 2008). (A longer version is available in CMU-MLD Technical Report 08-104 with the same title.)

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). (A longer version is available soon in CMU-MLD Technical Report 08-106 with the same title.)

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). (A longer version is available soon in CMU-MLD Technical Report 08-105 with the same title.)

P. Ray, S. Shringarpure, M. Kolar and E. P. Xing, CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing, PLoS Computational Biology, 4(6): e1000090. [pdf] [supplemental material] [software]

H. Kamisetty, E. P. Xing, C. J. Langmead, Free Energy Estimates of All-atom Protein Structures Using Generalized Belief Propagation, Journal of Computational Biology, 15(7): 755-766, 2008. [pdf]

F. Gou, 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).

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 (SDM2008).

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 (SDM2008).

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). [software]

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.

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.

2007

B. Zhao and E. P. Xing, HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation, Advances in Neural Information Processing Systems 20 (NIPS2007).

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).

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.

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). [software]

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).

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).

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).

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).

E. P. Xing, M. Jordan, and R. Roded, Bayesian Haplotype Inference via the Dirichlet Process, Journal of Computational Biology, Volume 14, Number 3, Pp. 267-284, 2007.

E. P. Xing and K. Sohn, Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space, Bayesian Analysis, Volunn 2, Number 2, 2007. A synopsis of this paper also appears in Bayesian Statistics 8, the Proc. Valencia / ISBA 8th World Meeting on Bayesian Statistics.

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).

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)

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).

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).

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).

F. Li, Y. Yang and E. P. Xing, Inferring regulatory networks using a hierarchical Bayesian graphical Gaussian model, CMU-MLD Technical Report 06-117.

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.

E. P. Xing and K. Sohn, A New Nonparametric Bayesian Model for Genetic Inference in Open Ancestral Space, CMU-MLD Technical Report 06-111.

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). (full oral presentation, top 3%)

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).

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).

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)).

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).

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).

G. Fan and E.P Xing, Bayesian Exponential Family Harmoniums, CMU-MLD Technical Report 06-103.

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).

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).

2005

E.P. Xing, On Topic Evolution. CMU-CALD Technical Report 05-115.

E.P. Xing, Dynamic Nonparametric Bayesian Models and the Birth-Death Process. CMU-CALD Technical Report 05-114.

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 (28 Dec, 2005).

F. Li, Y. Yang and E. P. Xing, From Lasso regression to Feature vector machine, Advances in Neural Information Processing Systems 18 (NIPS2005).

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 (26 Jul, 2005)

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).

E.P. Xing, R. Yan and A. G. Hauptmann, Mining Associated Text and Images with Dual-Wing Harmoniums. Uncertainty in Artificial Intelligence, 2005 (UAI2005).

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).

B. Zhao, E.P Xing, and A. Waibel, Bilingual Word Spectral Clustering for Statistical Machine Translation. ACL-Workshop-WPT, Ann Arbor MI, 2005.

2004

E.P. Xing, Probabilistic graphical models and algorithms for genomic analysis. Ph.D. Thesis, University of California, Berkeley, July 2004.

E.P. Xing, M.I Jordan and S. Russell, Graph partition strategies for generalized mean field inference. Uncertainty in Artificial Intelligence 20 (UAI2004), (eds. Meek and Halpern) AUAI Press, 602-610, 2004. [ps]

E.P. Xing, R. Sharan and M.I Jordan, Bayesian Haplotype Inference via the Dirichlet Process. Proceedings of the 21st International Conference on Machine Learning (ICML2004), (eds. Greiner and Schuurmans), ACM Press, 879-886, [ps]. An earlier version of this paper also appeared as a book chapter in Lecture Notes in Bioinformatics, Special issue for 2nd RECOMB Satellite Workshop on Computational Methods for SNPs and Haplotypes, 2004. (ps).

E.P. Xing and R. M. Karp, MotifPrototyper: a profile Bayesian model for motif family. Proc. Natl. Acad. Sci. vol. 101, no. 29, 10523-10528, 2004. [pnas site].

2003

E.P. Xing, M.I. Jordan, and S. Russell, A generalized mean field algorithm for variational inference in exponential families, Uncertainty in Artificial Intelligence (UAI2003), (eds. Meek and Kjaelff) Morgan Kaufmann Publishers, 583-591, 2003. (This paper was awarded a Runner-up Best Student Paper Award.) (ps, code.)

E.P. Xing and M.I Jordan, On semidefinite relaxation for normalized k-cut and connections to spectral clustering. Technical Report CSD-03-1265, Division of Computer Science, University of California, Berkeley, 2003. (ps)

E.P. Xing, W. Wu, M.I. Jordan and R.M. Karp, LOGOS: A modular Bayesian model for de novo motif detection. Journal of Bioinformatics and Computational biology 2004, 2(1), 127-154. An earlier version of this paper was also presented in IEEE Computer Society Bioinformatics Conference, CSB2003. (ps)

E.P. Xing, Feature Selection in Microarray Analysis, in D.P. Berrar, W. Dubitzky and M. Granzow (Eds.), A Practical Approach to Microarray Data Analysis, Kluwer Academic Publishers, 2003.

2002

E.P. Xing, M.I. Jordan, R.M. Karp and S. Russell, A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences. Advances in Neural Information Processing Systems 16 (NIPS2002), (eds. Becker et al.) MIT Press, 2002. (ps) A long version with more biological results is available here.

E.P. Xing, A.Y. Ng, M.I. Jordan and S. Russell, Distance Metric Learning, with application to Clustering with side-information, Advances in Neural Information Processing Systems 16 (NIPS2002), (eds. Becker et al.) MIT Press, 521-528, 2002. (ps, data, code.)

2001

E.P. Xing, M.I. Jordan and R.M. Karp, Feature selection for high-dimensional genomic microarray data, Proceedings of the Eighteenth International Conference on Machine Learning, (ICML2001). (ps)

E.P. Xing and R.M. Karp, CLIFF: Clustering of High-Dimensional Microarray Data via Iterative Feature Filtering Using Normalized Cuts, Bioinformatics 17 Suppl 1:S306-15, 2001. (special issue for The Ninth International Conference on Intelligence Systems for Molecular Biology, (ISMB 2001)).

E.P. Xing, D. Wolf, I. Dubchak, S. Spengler, M. Zorn, C. Kulikowski, I. Muchnik, Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation, Journal of Theoretical Biology, 21;212(2):129-39, 2001.

pre2000

E.P. Xing, C. Kulikowski, I. Muchnik, I. Dubchak, D. Wolf, S. Spengler and M. Zorn, Analysis of ribosomal RNA sequences by combinatorial clustering, Proceedings, The Seventh International Conference on Intelligence Systems for Molecular Biology (ISMB99), (Eds. T. Lengauer et al.) AAAI/MIT Press, Menlo Park, CA. P. 287-296, 1999.

E.P. Xing, Y. Nie, Y-L Song, G-Y. Yang, C. C. Cai, L-D. Wang, C. S. Chung, Mechanisms of inactivation of p14^ARF, p15^INK4b and p16^INK4a genes in human esophageal squamous cell carcinoma: p14^ARF is potentially another inactivation hotspot within the 9p21 gene cluster, Clinical Cancer Research, 1999 Oct; 5(10): 2704-13.

E. P. Xing, G-Y. Yang, L-D. Wang, C. S. Yang, Loss of Heterozygous of the Rb gene correlates with pRb protein expression and associates with p53 alteration in human esophageal cancer, Clinical Cancer Research, 1999 May; 5(5): 1231-40.

E. P. Xing, Y. Nie, L-D. Wang, G-Y. Yang, C.S. Yang, Aberrant methylation of p16^INK4a and deletion of p15^INK4b are frequent events in human esophageal cancer, Carcinogenesis, 1999 Jan; 20(1): 77-84.

Last updated 11/28/09