Jason M. Klusowski

According to our database, Jason M. Klusowski authored at least 26 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Challenges in Variable Importance Ranking Under Correlation.

Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski

CoRR, 2024

Stochastic Gradient Descent for Additive Nonparametric Regression.

Xin Chen, Jason M. Klusowski

CoRR, 2024

2023

Robust Transfer Learning with Unreliable Source Data.

Jianqing Fan, Cheng Gao, Jason M. Klusowski

CoRR, 2023

Error Reduction from Stacked Regressions.

Xin Chen, Jason M. Klusowski, Yan Shuo Tan

CoRR, 2023

On the Implicit Bias of Adam.

Matias D. Cattaneo, Jason M. Klusowski, Boris Shigida

CoRR, 2023

Sharp Convergence Rates for Matching Pursuit.

Jason M. Klusowski, Jonathan W. Siegel

CoRR, 2023

2022

On the Pointwise Behavior of Recursive Partitioning and Its Implications for Heterogeneous Causal Effect Estimation.

Matias D. Cattaneo, Jason M. Klusowski, Peter M. Tian

CoRR, 2022

2021

Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing.

Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su

IEEE Trans. Inf. Theory, 2021

Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit.

Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su

CoRR, 2021

Universal Consistency of Decision Trees for High Dimensional Additive Models.

Jason M. Klusowski

CoRR, 2021

Good Classifiers are Abundant in the Interpolating Regime.

Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Nonparametric Variable Screening with Optimal Decision Stumps.

Jason M. Klusowski, Peter M. Tian

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Sharp Analysis of a Simple Model for Random Forests.

Jason M. Klusowski

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Good linear classifiers are abundant in the interpolating regime.

Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney

CoRR, 2020

Sparse Learning with CART.

Jason M. Klusowski

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization.

Jason M. Klusowski, Dana Yang, W. D. Brinda

IEEE Trans. Inf. Theory, 2019

Global Capacity Measures for Deep ReLU Networks via Path Sampling.

Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher

CoRR, 2019

Best Split Nodes for Regression Trees.

Jason M. Klusowski

CoRR, 2019

Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation.

Andrew R. Barron, Jason M. Klusowski

CoRR, 2019

2018

Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With ℓ¹ and ℓ⁰ Controls.

Jason M. Klusowski, Andrew R. Barron

IEEE Trans. Inf. Theory, 2018

Finite-Sample Risk Bounds for Maximum Likelihood Estimation With Arbitrary Penalties.

W. D. Brinda, Jason M. Klusowski

IEEE Trans. Inf. Theory, 2018

Approximation and Estimation for High-Dimensional Deep Learning Networks.

Andrew R. Barron, Jason M. Klusowski

CoRR, 2018

Complete Analysis of a Random Forest Model.

Jason M. Klusowski

CoRR, 2018

Estimating the Number of Connected Components in a Graph via Subgraph Sampling.

Jason M. Klusowski, Yihong Wu

CoRR, 2018

Counting Motifs with Graph Sampling.

Jason M. Klusowski, Yihong Wu

Proceedings of the Conference On Learning Theory, 2018

2017

Minimax lower bounds for ridge combinations including neural nets.

Jason M. Klusowski, Andrew R. Barron

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017