Jason M. Klusowski

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Andrew R BarronProfessor of Statistics, Yale UniversityVerifisert e-postadresse på yale.edu
Matias D. CattaneoPrinceton UniversityVerifisert e-postadresse på princeton.edu
Dana YangAssistant Professor, Cornell UniversityVerifisert e-postadresse på cornell.edu
Weijie SuAssociate Professor, University of PennsylvaniaVerifisert e-postadresse på wharton.upenn.edu
Cynthia RushColumbia UniversityVerifisert e-postadresse på columbia.edu
Zhiqi BuAmazon AGIVerifisert e-postadresse på sas.upenn.edu
Yihong WuProfessor, Department of Statistics and Data ScienceVerifisert e-postadresse på yale.edu
Ryan TheisenUniversity of California, BerkeleyVerifisert e-postadresse på berkeley.edu
Rajita ChandakEPFLVerifisert e-postadresse på epfl.ch
Jianqing FanProfessor of Statistics, Professor of Finance, Princeton UniversityVerifisert e-postadresse på princeton.edu
Michael MahoneyProfessor of Statistics, UC BerkeleyVerifisert e-postadresse på stat.berkeley.edu
Boris ShigidaPhD Student, Princeton UniversityVerifisert e-postadresse på princeton.edu
Victor-Emmanuel BrunelENSAE-CREST, Professor in StatisticsVerifisert e-postadresse på ensae.fr
William G UnderwoodUniversity of CambridgeVerifisert e-postadresse på cam.ac.uk
Mengdi WangCenter for Statistics & Machine Learning, ECE, Princeton UniversityVerifisert e-postadresse på princeton.edu
Yuan CaoThe University of Hong KongVerifisert e-postadresse på hku.hk
Han LiuOrrington Lunt Professor of Computer Science, Statistics and Data Science, Northwestern UniversityVerifisert e-postadresse på northwestern.edu
Zihao LiPrinceton UniversityVerifisert e-postadresse på princeton.edu
Yan Shuo TanAssistant Professor, National University of SingaporeVerifisert e-postadresse på nus.edu.sg
Caiming XiongSalesforce ResearchVerifisert e-postadresse på salesforce.com

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Jason M. Klusowski

Assistant Professor, Department of Operations Research & Financial Engineering

Verifisert e-postadresse på princeton.edu - Startside

statistics probability machine learning information theory


Tittel Sorter etter sitater Sorter etter år Sorter etter tittel	Sitert av Sitert av	År
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	190*	2018
Approximation and estimation for high-dimensional deep learning networks AR Barron, JM Klusowski arXiv preprint arXiv:1809.03090, 2018	76	2018
Risk bounds for high-dimensional ridge function combinations including neural networks JM Klusowski, AR Barron arXiv preprint arXiv:1607.01434, 2016	75	2016
Sharp analysis of a simple model for random forests J Klusowski International Conference on Artificial Intelligence and Statistics, 757-765, 2021	72*	2021
Large scale prediction with decision trees JM Klusowski, PM Tian Journal of the American Statistical Association 119 (545), 525-537, 2024	64*	2024
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	62	2019
Algorithmic analysis and statistical estimation of SLOPE via approximate message passing Z Bu, JM Klusowski, C Rush, WJ Su IEEE Transactions on Information Theory 67 (1), 506-537, 2020	59	2020
Complexity, statistical risk, and metric entropy of deep nets using total path variation AR Barron, JM Klusowski arXiv preprint arXiv:1902.00800, 2019	35	2019
Counting motifs with graph sampling JM Klusowski, Y Wu Conference On Learning Theory, 1966-2011, 2018	31	2018
Statistical guarantees for estimating the centers of a two-component Gaussian mixture by EM JM Klusowski, WD Brinda arXiv preprint arXiv:1608.02280, 2016	27	2016
Sparse learning with CART J Klusowski Advances in Neural Information Processing Systems 33, 11612-11622, 2020	23	2020
On the implicit bias of adam MD Cattaneo, JM Klusowski, B Shigida arXiv preprint arXiv:2309.00079, 2023	20	2023
Minimax lower bounds for ridge combinations including neural nets JM Klusowski, AR Barron 2017 IEEE International Symposium on Information Theory (ISIT), 1376-1380, 2017	18	2017
Estimating the number of connected components in a graph via subgraph sampling JM Klusowski, Y Wu	17	2020
Convergence rates of oblique regression trees for flexible function libraries MD Cattaneo, R Chandak, JM Klusowski The Annals of Statistics 52 (2), 466-490, 2024	13	2024
Inference with mondrian random forests MD Cattaneo, JM Klusowski, WG Underwood arXiv preprint arXiv:2310.09702, 2023	12	2023
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	11	2023
On the pointwise behavior of recursive partitioning and its implications for heterogeneous causal effect estimation MD Cattaneo, JM Klusowski, PM Tian arXiv preprint arXiv:2211.10805, 2022	11	2022
Good classifiers are abundant in the interpolating regime R Theisen, J Klusowski, M Mahoney International Conference on Artificial Intelligence and Statistics, 3376-3384, 2021	11*	2021
Analyzing cart JM Klusowski arXiv preprint arXiv:1906.10086, 2019	11	2019

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