Publications

(2020). Estimation of a Low-rank Topic-Based Model for Information Cascades. Journal of Machine Learning Research.

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(2020). Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. International Conference on Machine Learning.

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(2020). Posterior Ratio Estimation for Latent Variables. arXiv:2002.06410.

(2019). Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model. Journal of the American Statistical Association.

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(2019). Tensor Canonical Correlation Analysis. arXiv:1906.05358.

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(2019). Partially Linear Additive Gaussian Graphical Models. Proceedings of the 36th International Conference on Machine Learning.

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(2019). Learning Influence-Receptivity Network Structure with Guarantee. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics.

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(2019). High-dimensional Varying Index Coefficient Models via Stein's Identity. Journal of Machine Learning Research.

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(2019). Direct Estimation of Differential Functional Graphical Models. Advances in Neural Information Processing Systems 32.

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(2019). Convergent Policy Optimization for Safe Reinforcement Learning. Advances in Neural Information Processing Systems 32.

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(2018). Provable Gaussian Embedding with One Observation. Advances in Neural Information Processing Systems 31.

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(2018). Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models. Journal of Machine Learning Research.

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(2018). Joint Nonparametric Precision Matrix Estimation with Confounding. Uncertainty in Artificial Intelligence.

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(2017). Efficient Distributed Learning with Sparsity. Proceedings of the 34th International Conference on Machine Learning.

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(2017). Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics.

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(2017). The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities. Advances in Neural Information Processing Systems 30.

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(2017). Recovering block-structured activations using compressive measurements. Electron. J. Statist.

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(2017). An Influence-Receptivity Model for Topic based Information Cascades. 2017 IEEE International Conference on Data Mining.

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(2016). Distributed Multi-Task Learning. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics.

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(2016). Statistical Inference for Pairwise Graphical Models Using Score Matching. Advances in Neural Information Processing Systems 29.

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(2016). Inference for High-dimensional Exponential Family Graphical Models. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics.

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(2015). Learning structured densities via infinite dimensional exponential families. Advances in Neural Information Processing Systems 28.

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(2014). Graph Estimation From Multi-attribute Data. J. Mach. Learn. Res.

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(2014). Berry-Esseen bounds for estimating undirected graphs. Electron. J. Stat.

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(2013). Markov Network Estimation From Multi-attribute Data. Proceedings of the 30th International Conference on Machine Learning.

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(2013). Feature Selection in High-Dimensional Classification. Proceedings of the 30th International Conference on Machine Learning.

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(2012). Variance Function Estimation in High-dimensions. Proceedings of the 29th International Conference on Machine Learning.

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(2012). Consistent Covariance Selection From Data With Missing Values. Proceedings of the 29th International Conference on Machine Learning.

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(2012). Marginal Regression For Multitask Learning. Proceedings of the 15th International Conference on Artificial Intelligence and Statistics.

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(2012). Estimating Networks With Jumps. Electron. J. Stat.

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(2011). Union Support Recovery In Multi-task Learning. J. Mach. Learn. Res.

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(2011). Statistical and computational tradeoffs in biclustering. NIPS 2011 Workshop on Computational Trade-offs in Statistical Learning.

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(2011). On Time Varying Undirected Graphs. Proceedings of the 14th International Conference on Artificial Intelligence and Statistics.

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(2011). Minimax Localization of Structural Information in Large Noisy Matrices. Advances in Neural Information Processing Systems 24.

(2010). On Sparse Nonparametric Conditional Covariance Selection. Proc. 27th Int. Conf. Mach. Learn..

(2010). Estimating Time-varying Networks. Ann. Appl. Stat.

(2009). Sparsistent Estimation Of Time-varying Discrete Markov Random Fields. ArXiv e-prints, arXiv:0907.2337.

(2009). KELLER: estimating time-varying interactions between genes. Bioinformatics.

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(2009). Time-varying Dynamic Bayesian Networks. Proc. of NIPS.

(2008). CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing. PLoS Computational Biology.

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(2006). Comparison of collocation extraction measures for document indexing. 28th International Conference on Information Technology Interfaces, 2006..

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(2005). Computer-Aided document Indexing Systems. Journal of Computing and Information Technology.