Selected Bibliography for Mladen Kolar

Associate Professor of Econometrics and Statistics

Home page of Mladen Kolar
Mladen Kolar author profile at Scopus

Published Works

"FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting." Boxin Zhao, Y. Samuel Wang and Mladen Kolar; Journal of Machine Learning Research, 2022, 23(82), pp. 1-82.

"A Nonconvex Framework for Structured Dynamic Covariance Recovery." Katherine Tsai, Mladen Kolar and Oluwasanmi Koyejo; Journal of Machine Learning Research, 2022, 23(200), pp. 1-91.

"An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians." Sen Na, Mihai Anitescu and Mladen Kolar; Mathematical Programming, 2022.

"Provably Training Overparameterized Neural Network Classifiers with Non-Convex Constraints." You-Lin Chen, Zhaoran Wang and Mladen Kolar; Electronic Journal of Statistics, 2022, 16(2), pp. 5812-51.

"Joint Gaussian Graphical Model Estimation: A Survey." Katherine Tsai, Oluwasanmi Koyejo and Mladen Kolar; WIREs Computational Statistics, 2022, 14(6), pp. e1582.

"Dynamic Regret Minimization for Control of Non-Stationary Linear Dynamical Systems." Yuwei Luo, Varun Gupta and Mladen Kolar; Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2022, 6(1), pp. 1–72.

"Tensor Canonical Correlation Analysis with Convergence and Statistical Guarantees." You-Lin Chen, Mladen Kolar and Ruey S. Tsay; Journal of Computational and Graphical Statistics, 2021, 30(3), pp. 728-44.

"High-Dimensional Index Volatility Models Via Stein’s Identity." Sen Na and Mladen Kolar; Bernoulli, 2021, 27(2), pp. 794-817.

"Two-Sample Inference for High-Dimensional Markov Networks." Byol Kim, Song Liu and Mladen Kolar; Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2021, 83(5), pp. 939-62.

"Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model." Junwei Lu, Mladen Kolar and Han Liu; Journal of the American Statistical Association, 2020, 115(532), pp. 2084-99.

"Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees," Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang and Mladen Kolar, Proceedings of the 37th International Conference on Machine Learning Editor, JMLR.org, 2020 of Conference, pp. Pages.

"Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach," Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Zhaoran Wang and Mladen Kolar, Proceedings of the 34th International Conference on Neural Information Processing Systems Editor, Vancouver, BC, Canada: Curran Associates Inc., 2020 of Conference, pp. Pages.

"Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching." Ming Yu, Varun Gupta and Mladen Kolar; Journal of Machine Learning Research, 2020, 21(1), pp. Article 91.

"Estimation of a Low-Rank Topic-Based Model for Information Cascades." Ming Yu, Varun Gupta and Mladen Kolar; Journal of Machine Learning Research, 2020, 21(1), pp. Article 71.

"Convergent Policy Optimization for Safe Reinforcement Learning," Ming Yu, Zhuoran Yang, Mladen Kolar and Zhaoran Wang, Advances in Neural Information Processing Systems Editor, Curran Associates, Inc., 2019 of Conference, pp. Pages.

"Direct Estimation of Differential Functional Graphical Models," Boxin Zhao, Y. Samuel Wang and Mladen Kolar, Advances in Neural Information Processing Systems Editor, Curran Associates, Inc., 2019 of Conference, pp. Pages.

"Direct Estimation of Differential Functional Graphical Models," Boxin Zhao, Y. Samuel Wang and Mladen Kolar, in Proceedings of the 33rd International Conference on Neural Information Processing Systems. Curran Associates Inc., 2019, pp. Article 231.

"Convergent Policy Optimization for Safe Reinforcement Learning," Ming Yu, Zhuoran Yang, Mladen Kolar and Zhaoran Wang, in Proceedings of the 33rd International Conference on Neural Information Processing Systems. Curran Associates Inc., 2019, pp. Article 281.

"Rocket: Robust Confidence Intervals Via Kendall’s Tau for Transelliptical Graphical Models." Rina Foygel Barber and Mladen Kolar; The Annals of Statistics, 2018, 46(6B), pp. 3422-50.

"Provable Gaussian Embedding with One Observation," Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar and Zhaoran Wang, Proceedings of the 32nd International Conference on Neural Information Processing Systems Editor, Montréal, Canada: Curran Associates Inc., 2018 of Conference, pp. Pages.

"Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-Dimensional Data." Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar and Nathan Srebro; Electronic Journal of Statistics, 2017, 11(2), pp. 4896-944.

"Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models." Junwei Lu, Mladen Kolar and Han Liu; Journal of Machine Learning Research, 2017, 18(1), pp. 7401–78.

"Efficient Distributed Learning with Sparsity," Jialei Wang, Mladen Kolar, Nathan Srebro and Tong Zhang, Proceedings of the 34th International Conference on Machine Learning - Volume 70 Editor, Sydney, NSW, Australia: JMLR.org, 2017 of Conference, pp. Pages.

"The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities," Arun Sai Suggala, Mladen Kolar and Pradeep Ravikumar, Proceedings of the 31st International Conference on Neural Information Processing Systems Editor, Long Beach, California, USA: Curran Associates Inc., 2017 of Conference, pp. Pages.

"An Influence-Receptivity Model for Topic Based Information Cascades," Ming Yu, Varun Gupta and Mladen Kolar, 2017 IEEE International Conference on Data Mining (ICDM) 2017, pp. 1141-46.

"Discussion of “Coauthorship and Citation Networks for Statisticians”." Mladen Kolar and Matt Taddy; The Annals of Applied Statistics, 2016, 10(4), pp. 1835-41.

"Optimal Feature Selection in High-Dimensional Discriminant Analysis." Mladen Kolar and Han Liu; IEEE Transactions on Information Theory, 2015, 61(2), pp. 1063-83.

"Optimal Variable Selection in Multi-Group Sparse Discriminant Analysis." Irina Gaynanova and Mladen Kolar; Electronic Journal of Statistics, 2015, 9(2), pp. 2007-34.

"Learning Structured Densities Via Infinite Dimensional Exponential Families," Siqi Sun, Mladen Kolar and Jinbo Xu, Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 2 Editor, Montreal, Canada: MIT Press, 2015 of Conference, pp. Pages.

"Berry-Esseen Bounds for Estimating Undirected Graphs." Larry Wasserman, Mladen Kolar and Alessandro Rinaldo; Electronic Journal of Statistics, 2014, 8(1), pp. 1188-224.

"Graph Estimation from Multi-Attribute Data." Mladen Kolar, Han Liu and Eric P. Xing; Journal of Machine Learning Research, 2014, 15(1), pp. 1713–50.

"Feature Selection in High-Dimensional Classification," Mladen Kolar and Han Liu, Proceedings of the 30th International Conference on International Conference on Machine Learning - Volume 28 Editor, Atlanta, GA, USA: JMLR.org, 2013 of Conference, pp. Pages.

"Markov Network Estimation from Multi-Attribute Data," Mladen Kolar, Han Liu and Eric P. Xing, Proceedings of the 30th International Conference on International Conference on Machine Learning - Volume 28 Editor, Atlanta, GA, USA: JMLR.org, 2013 of Conference, pp. Pages.

Uncovering Structure in High-Dimensions: Networks and Multi-Task Learning Problems; Mladen Kolar; Ph.D Dissertation, Carnegie Mellon University, 2013.

"Estimating Sparse Precision Matrices from Data with Missing Values," Mladen Kolar and Eric P. Xing, Proceedings of the 29th International Coference on International Conference on Machine Learning Editor, Edinburgh, Scotland: Omnipress, 2012 of Conference, pp. Pages.

"Variance Function Estimation in High-Dimensions," Mladen Kolar and James Sharpnack, Proceedings of the 29th International Coference on International Conference on Machine Learning Editor, Edinburgh, Scotland: Omnipress, 2012 of Conference, pp. Pages.

"Estimating Networks with Jumps." Mladen Kolar and Eric P. Xing; Electronic Journal of Statistics, 2012, 6, pp. 2069--106.

"Minimax Localization of Structural Information in Large Noisy Matrices," Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo and Aarti Singh, Proceedings of the 24th International Conference on Neural Information Processing Systems Editor, Granada, Spain: Curran Associates Inc., 2011 of Conference, pp. Pages.

"Union Support Recovery in Multi-Task Learning." Mladen Kolar, John Lafferty and Larry Wasserman; Journal of Machine Learning Research, 2011, 12, pp. 2415-35.

"On Time Varying Undirected Graphs." Mladen Kolar and Eric P. Xing; Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011, pp. 407-15.

"On Sparse Nonparametric Conditional Covariance Selection," Mladen Kolar, Ankur P. Parikh and Eric P. Xing, Proceedings of the 27th International Conference on International Conference on Machine Learning Editor, Haifa, Israel: Omnipress, 2010 of Conference, pp. Pages.

"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, 2010, 9, pp. 413-20.

"Estimating Time-Varying Networks." Mladen Kolar, Le Song, Amr Ahmed and Eric P. Xing; Annals of Applied Statistics, 2010, 4(1), pp. 94--123.

"Sparsistent Learning of Varying-Coefficient Models with Structural Changes," Mladen Kolar, Le Song and Eric Xing, in Advances in Neural Information Processing Systems 22. Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams and A. Culotta, 2009, pp. 1006-14.

"Time-Varying Dynamic Bayesian Networks," Le Song, Mladen Kolar and Eric Xing, in Advances in Neural Information Processing Systems 22. Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams and A. Culotta, 2009, pp. 1732-40.

"Keller: Estimating Time-Varying Interactions between Genes." Le Song, Mladen Kolar and Eric P. Xing; Bioinformatics, 2009, 25(12), pp. i128-i36.

"Csmet: Comparative Genomic Motif Detection Via Multi-Resolution Phylogenetic Shadowing." Pradipta Ray, Suyash Shringarpure, Mladen Kolar and Eric P. Xing; PLoS Computational Biology, 2008, 4(6), pp. e1000090.