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All publications by Eric P. Xing
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The Human Kernel
Andrew G. Wilson, Christoph Dann, Chris Lucas and Eric P. Xing
Advances in Neural Information Processing Systems 28, 2015


On Model Parallelization and Scheduling Strategies for Distributed Machine Learning
Seunghak Lee, Jin K. Kim, Xun Zheng, Qirong Ho, Garth A. Gibson and Eric P. Xing
Advances in Neural Information Processing Systems 27, 2014


Dependent nonparametric trees for dynamic hierarchical clustering
Kumar Dubey, Qirong Ho, Sinead A. Williamson and Eric P. Xing
Advances in Neural Information Processing Systems 27, 2014


Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models
Sinead Williamson, Avinava Dubey and Eric P. Xing
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks
Qirong Ho, Junming Yin and Eric P. Xing
Advances in Neural Information Processing Systems 25, 2012


Monte Carlo Methods for Maximum Margin Supervised Topic Models
Qixia Jiang, Jun Zhu, Maosong Sun and Eric P. Xing
Advances in Neural Information Processing Systems 25, 2012


Symmetric Correspondence Topic Models for Multilingual Text Analysis
Kosuke Fukumasu, Koji Eguchi and Eric P. Xing
Advances in Neural Information Processing Systems 25, 2012


Group Sparse Additive Models
Junming Yin, Xi Chen and Eric P. Xing
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Consistent Covariance Selection From Data With Missing Values
Mladen Kolar and Eric P. Xing
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Kernel Embeddings of Latent Tree Graphical Models
Le Song, Eric P. Xing and Ankur P. Parikh
Advances in Neural Information Processing Systems 24, 2011


Infinite Latent SVM for Classification and Multi-task Learning
Jun Zhu, Ning Chen and Eric P. Xing
Advances in Neural Information Processing Systems 24, 2011


Large-Scale Category Structure Aware Image Categorization
Bin Zhao, Fei Li and Eric P. Xing
Advances in Neural Information Processing Systems 24, 2011


Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines
Jun Zhu, Ning Chen and Eric P. Xing
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


A Spectral Algorithm for Latent Tree Graphical Models
Le Song, Eric P. Xing and Ankur P. Parikh
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


An Augmented Lagrangian Approach to Constrained MAP Inference
Pedro Aguiar, Eric P. Xing, Mário Figueiredo, Noah A. Smith and André Martins
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Approximating Correlated Equilibria using Relaxations on the Marginal Polytope
Hetunandan Kamisetty, Eric P. Xing and Christopher J. Langmead
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Sparse Additive Generative Models of Text
Jacob Eisenstein, Amr Ahmed and Eric P. Xing
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Online Learning of Structured Predictors with Multiple Kernels
André Martins, Noah A. Smith, Eric P. Xing, Pedro Aguiar and Mário Figueiredo
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


On Time Varying Undirected Graphs
Mladen Kolar and Eric P. Xing
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks
Qirong Ho, Le Song and Eric P. Xing
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Multiscale Community Blockmodel for Network Exploration
Qirong Ho, Ankur P. Parikh, Le Song and Eric P. Xing
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text
Amr Ahmed, Qirong Ho, Choon H. Teo, Jacob Eisenstein, Eric P. Xing and Alex J. Smola
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Conditional Topic Random Fields
Jun Zhu and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


On Sparse Nonparametric Conditional Covariance Selection
Mladen Kolar, Ankur P. Parikh and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
Seyoung Kim and Eric P. Xing
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Adaptive Multi-Task Lasso: with Application to eQTL Detection
Seunghak Lee, Jun Zhu and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Predictive Subspace Learning for Multi-view Data: a Large Margin Approach
Ning Chen, Jun Zhu and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Large Margin Learning of Upstream Scene Understanding Models
Jun Zhu, Li-jia Li, Li Fei-fei and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
Li-jia Li, Hao Su, Li Fei-fei and Eric P. Xing
Advances in Neural Information Processing Systems 23, 2010


Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach
Mladen Kolar and Eric P. Xing
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Maximum Entropy Discrimination Markov Networks
Jun Zhu and Eric P. Xing
Journal of Machine Learning Research, 2009


Nonextensive Information Theoretic Kernels on Measures
André Martins, Noah A. Smith, Eric P. Xing, Pedro Aguiar and Mário Figueiredo
Journal of Machine Learning Research, 2009


On primal and dual sparsity of Markov networks
Jun Zhu and Eric P. Xing
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


MedLDA: maximum margin supervised topic models for regression and classification
Jun Zhu, Amr Ahmed and Eric P. Xing
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Polyhedral outer approximations with application to natural language parsing
André Martins, Noah A. Smith and Eric P. Xing
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Dynamic mixed membership blockmodel for evolving networks
Wenjie Fu, Le Song and Eric P. Xing
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Heterogeneous multitask learning with joint sparsity constraints
Xiaolin Yang, Seyoung Kim and Eric P. Xing
Advances in Neural Information Processing Systems 22, 2009


Time-Varying Dynamic Bayesian Networks
Le Song, Mladen Kolar and Eric P. Xing
Advances in Neural Information Processing Systems 22, 2009


Sparsistent Learning of Varying-coefficient Models with Structural Changes
Mladen Kolar, Le Song and Eric P. Xing
Advances in Neural Information Processing Systems 22, 2009


Network Completion and Survey Sampling
Steve Hanneke and Eric P. Xing
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Laplace maximum margin Markov networks
Jun Zhu, Eric P. Xing and Bo Zhang
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


{\it mStruct}: a new admixture model for inference of population structure in light of both genetic admixing and allele mutations
Suyash Shringarpure and Eric P. Xing
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Nonextensive entropic kernels
André Martins, Mário Figueiredo, Pedro Aguiar, Noah A. Smith and Eric P. Xing
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Mixed Membership Stochastic Blockmodels
Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing
Journal of Machine Learning Research, 2008


Partially Observed Maximum Entropy Discrimination Markov Networks
Jun Zhu, Eric P. Xing and Bo Zhang
Advances in Neural Information Processing Systems 21, 2008


Mixed Membership Stochastic Blockmodels
Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg and Eric P. Xing
Advances in Neural Information Processing Systems 21, 2008


Recovering temporally rewiring networks: a model-based approach
Fan Guo, Steve Hanneke, Wenjie Fu and Eric P. Xing
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
Bing Zhao and Eric P. Xing
Advances in Neural Information Processing Systems 20, 2007


Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model
Amr Ahmed and Eric P. Xing
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture
Eric P. Xing, Kyung-ah Sohn, Michael I. Jordan and Yee W. Teh
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space
Kyung-ah Sohn and Eric P. Xing
Advances in Neural Information Processing Systems 19, 2006


Predicting protein folds with structural repeats using a chain graph model
Yan Liu, Eric P. Xing and Jaime G. Carbonell
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


From Lasso regression to Feature vector machine
Fan Li, Yiming Yang and Eric P. Xing
Advances in Neural Information Processing Systems 18, 2005


Bayesian haplo-type inference via the dirichlet process
Eric P. Xing, Roded Sharan and Michael I. Jordan
Proceedings of the 21st International Conference on Machine Learning (ICML-04), 2004


A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences
Eric P. Xing, Michael I. Jordan, Richard M. Karp and Stuart Russell
Advances in Neural Information Processing Systems 15, 2002


Distance Metric Learning with Application to Clustering with Side-Information
Eric P. Xing, Michael I. Jordan, Stuart Russell and Andrew Y. Ng
Advances in Neural Information Processing Systems 15, 2002