Mladen Kolar

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Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Han LiuProfessor, Department of Computer Science and Department of Statistics, Northwestern UniversityVerified email at northwestern.edu
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Ming YuThe University of Chicago Booth School of BusinessVerified email at chicagobooth.edu
Jialei WangUniversity of ChicagoVerified email at uchicago.edu
Sen NaPostdoc ResearcherVerified email at berkeley.edu
Zhuoran YangYale UniversityVerified email at yale.edu
Varun GuptaAssociate Professor, Booth School of Business, University of ChicagoVerified email at uchicago.edu
Alessandro RinaldoThe University of Texas at AustinVerified email at austin.utexas.edu
Boxin ZhaoUniversity of ChicagoVerified email at uchicago.edu
Zhaoran WangAssistant Professor at Northwestern UniversityVerified email at northwestern.edu
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon UniversityVerified email at cmu.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityVerified email at stat.cmu.edu
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Junwei LuAssistant Professor of Biostatistics, Harvard T.H. Chan School of Public HealthVerified email at hsph.harvard.edu
Luofeng LiaoColumbia UniversityVerified email at columbia.edu
Sanmi KoyejoAssistant Professor, Stanford UniversityVerified email at stanford.edu
Amr AhmedSenior Staff Research Scientist, Google AIVerified email at google.com
Y. Samuel WangCornell UniversityVerified email at cornell.edu

Mladen Kolar

The University of Chicago, Booth School of Business

Verified email at chicagobooth.edu - Homepage

Machine learning Statistics


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Estimating time-varying networks M Kolar, L Song, A Ahmed, EP Xing The Annals of Applied Statistics, 94-123, 2010	347	2010
Time-varying dynamic bayesian networks L Song, M Kolar, E Xing Advances in neural information processing systems 22, 2009	238	2009
Efficient distributed learning with sparsity J Wang, M Kolar, N Srebro, T Zhang International conference on machine learning, 3636-3645, 2017	141	2017
KELLER: estimating time-varying interactions between genes L Song, M Kolar, EP Xing Bioinformatics 25 (12), i128-i136, 2009	136	2009
Convergent policy optimization for safe reinforcement learning M Yu, Z Yang, M Kolar, Z Wang Advances in Neural Information Processing Systems 32, 2019	93	2019
Distributed multi-task learning J Wang, M Kolar, N Srerbo Artificial intelligence and statistics, 751-760, 2016	74	2016
On time varying undirected graphs M Kolar, EP Xing Proceedings of the Fourteenth International Conference on Artificial …, 2011	71	2011
Sparsistent learning of varying-coefficient models with structural changes M Kolar, L Song, E Xing Advances in neural information processing systems 22, 2009	71	2009
Minimax localization of structural information in large noisy matrices M Kolar, S Balakrishnan, A Rinaldo, A Singh Advances in Neural Information Processing Systems 24, 2011	70	2011
Estimating networks with jumps M Kolar, EP Xing Electronic journal of statistics 6, 2069, 2012	67	2012
Estimating sparse precision matrices from data with missing values M Kolar, EP Xing International Conference on Machine Learning, 635-642, 2012	53*	2012
ROCKET: Robust confidence intervals via Kendall’s tau for transelliptical graphical models RF Barber, M Kolar	50	2018
Sketching meets random projection in the dual: A provable recovery algorithm for big and high-dimensional data J Wang, J Lee, M Mahdavi, M Kolar, N Srebro Artificial Intelligence and Statistics, 1150-1158, 2017	48	2017
Comparison of collocation extraction measures for document indexing S Petrovic, J Snajder, B Dalbelo-Basic, M Kolar 28th International Conference on Information Technology Interfaces, 2006 …, 2006	48	2006
Statistical inference for pairwise graphical models using score matching M Yu, V Gupta, M Kolar Advances in Neural Information Processing Systems 29, 2016	44	2016
Feature selection in high-dimensional classification M Kolar, H Liu International Conference on Machine Learning, 329-337, 2013	43*	2013
On sparse nonparametric conditional covariance selection M Kolar, A P Parikh, E P Xing Carnegie Mellon University, 2010	41	2010
Graph estimation from multi-attribute data M Kolar, H Liu, EP Xing Journal of Machine Learning Research, 2014	39	2014
Statistical and computational tradeoffs in biclustering S Balakrishnan, M Kolar, A Rinaldo, A Singh, L Wasserman NIPS 2011 workshop on computational trade-offs in statistical learning 4, 2011	39	2011
A general framework for robust testing and confidence regions in high-dimensional quantile regression T Zhao, M Kolar, H Liu arXiv preprint arXiv:1412.8724, 2014	38	2014

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