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Jason M. Klusowski
Jason M. Klusowski
Assistant Professor, Department of Operations Research & Financial Engineering
Verified email at princeton.edu - Homepage
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
165*2018
Risk bounds for high-dimensional ridge function combinations including neural networks
JM Klusowski, AR Barron
arXiv preprint arXiv:1607.01434, 2016
702016
Approximation and estimation for high-dimensional deep learning networks
AR Barron, JM Klusowski
arXiv preprint arXiv:1809.03090, 2018
682018
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
562020
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
542019
Sharp analysis of a simple model for random forests
J Klusowski
International Conference on Artificial Intelligence and Statistics, 757-765, 2021
53*2021
Large scale prediction with decision trees
JM Klusowski, PM Tian
Journal of the American Statistical Association 119 (545), 525-537, 2024
34*2024
Complexity, statistical risk, and metric entropy of deep nets using total path variation
AR Barron, JM Klusowski
arXiv preprint arXiv:1902.00800, 2019
292019
Counting motifs with graph sampling
JM Klusowski, Y Wu
Conference On Learning Theory, 1966-2011, 2018
282018
Statistical guarantees for estimating the centers of a two-component Gaussian mixture by EM
JM Klusowski, WD Brinda
arXiv preprint arXiv:1608.02280, 2016
232016
Sparse learning with CART
J Klusowski
Advances in Neural Information Processing Systems 33, 11612-11622, 2020
192020
Minimax lower bounds for ridge combinations including neural nets
JM Klusowski, AR Barron
2017 IEEE International Symposium on Information Theory (ISIT), 1376-1380, 2017
182017
Estimating the number of connected components in a graph via subgraph sampling
JM Klusowski, Y Wu
152020
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
102023
On the implicit bias of adam
MD Cattaneo, JM Klusowski, B Shigida
arXiv preprint arXiv:2309.00079, 2023
82023
Analyzing cart
JM Klusowski
arXiv preprint arXiv:1906.10086, 2019
82019
Estimation of convex supports from noisy measurements
VE Brunel, JM Klusowski, D Yang
72021
Good classifiers are abundant in the interpolating regime
R Theisen, J Klusowski, M Mahoney
International Conference on Artificial Intelligence and Statistics, 3376-3384, 2021
7*2021
Nonparametric variable screening with optimal decision stumps
J Klusowski, P Tian
International Conference on Artificial Intelligence and Statistics, 748-756, 2021
72021
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
52024
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