Jason M. Klusowski

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Andrew R BarronProfessor of Statistics, Yale UniversityVerified email at yale.edu
Dana YangAssistant Professor, Cornell UniversityVerified email at cornell.edu
Weijie SuAssociate Professor, Wharton and Computer Science, University of PennsylvaniaVerified email at wharton.upenn.edu
Cynthia RushColumbia UniversityVerified email at columbia.edu
Zhiqi BuAmazon AIVerified email at sas.upenn.edu
Yihong WuProfessor, Department of Statistics and Data ScienceVerified email at yale.edu
Peter M. TianPhD Student, Operations Research and Financial Engineering, Princeton UniversityVerified email at princeton.edu
Ryan TheisenUniversity of California, BerkeleyVerified email at berkeley.edu
Matias D. CattaneoPrinceton UniversityVerified email at princeton.edu
Victor-Emmanuel BrunelENSAE-CREST, Professor in StatisticsVerified email at ensae.fr
Michael MahoneyProfessor of Statistics, UC BerkeleyVerified email at stat.berkeley.edu
Caiming XiongSalesforce ResearchVerified email at salesforce.com
Nitish Shirish KeskarOpenAIVerified email at openai.com
Huan WangSalesforce ResearchVerified email at yale.edu
Richard Socheryou.comVerified email at stanford.edu
Rajita ChandakPrinceton UniversityVerified email at princeton.edu
Jonathan W. SiegelAssistant Professor, Texas A&M UniversityVerified email at tamu.edu
Boris ShigidaPhD Student, Princeton UniversityVerified email at princeton.edu
Yan Shuo TanAssistant Professor in Statistics, National University of SingaporeVerified email at berkeley.edu

Jason M. Klusowski

Assistant Professor, Department of Operations Research & Financial Engineering

Verified email at princeton.edu - Homepage

statistics probability machine learning information theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With and Controls JM Klusowski, AR Barron IEEE Transactions on Information Theory 64 (12), 7649-7656, 2018	121	2018
Approximation and estimation for high-dimensional deep learning networks AR Barron, JM Klusowski arXiv preprint arXiv:1809.03090, 2018	61	2018
Risk bounds for high-dimensional ridge function combinations including neural networks JM Klusowski, AR Barron arXiv preprint arXiv:1607.01434, 2016	60	2016
Algorithmic analysis and statistical estimation of slope via approximate message passing Z Bu, J Klusowski, C Rush, W Su Advances in Neural Information Processing Systems 32, 2019	48	2019
Estimating the coefficients of a mixture of two linear regressions by expectation maximization JM Klusowski, D Yang, WD Brinda IEEE Transactions on Information Theory 65 (6), 3515-3524, 2019	41	2019
Complexity, statistical risk, and metric entropy of deep nets using total path variation AR Barron, JM Klusowski arXiv preprint arXiv:1902.00800, 2019	26	2019
Counting motifs with graph sampling JM Klusowski, Y Wu Conference On Learning Theory, 1966-2011, 2018	24	2018
Sharp analysis of a simple model for random forests J Klusowski International Conference on Artificial Intelligence and Statistics, 757-765, 2021	22	2021
Statistical guarantees for estimating the centers of a two-component Gaussian mixture by EM JM Klusowski, WD Brinda arXiv preprint arXiv:1608.02280, 2016	22	2016
Complete analysis of a random forest model JM Klusowski arXiv preprint arXiv:1805.02587, 2018	21	2018
Minimax lower bounds for ridge combinations including neural nets JM Klusowski, AR Barron 2017 IEEE International Symposium on Information Theory (ISIT), 1376-1380, 2017	17	2017
Uniform approximation by neural networks activated by first and second order ridge splines JM Klusowski, AR Barron arXiv preprint arXiv:1607.07819, 2016	17	2016
Estimating the number of connected components in a graph via subgraph sampling JM Klusowski, Y Wu	15	2020
Sparse learning with CART J Klusowski Advances in Neural Information Processing Systems 33, 11612-11622, 2020	15	2020
Characterizing the SLOPE trade-off: A variational perspective and the Donoho–Tanner limit Z Bu, JM Klusowski, C Rush, WJ Su The Annals of Statistics 51 (1), 33-61, 2023	10	2023
Universal consistency of decision trees in high dimensions JM Klusowski arXiv preprint arXiv:2104.13881, 2021	7	2021
Analyzing cart JM Klusowski arXiv preprint arXiv:1906.10086, 2019	7	2019
Estimating the coefficients of a mixture of two linear regressions by expectation maximization JM Klusowski, D Yang, WD Brinda arXiv preprint arXiv:1704.08231, 2017	7	2017
Estimation of convex supports from noisy measurements VE Brunel, JM Klusowski, D Yang	6	2021
Nonparametric variable screening with optimal decision stumps J Klusowski, P Tian International Conference on Artificial Intelligence and Statistics, 748-756, 2021	6	2021

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