Jason M. Klusowski

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 32

Top Topics

Decision Stumps

Linear Classifiers

Additive Models

Top Venues

IEEE Trans. Inf. Theory

Publications

Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski
Challenges in Variable Importance Ranking Under Correlation. CoRR (2024)
Xin Chen, Jason M. Klusowski
Stochastic Gradient Descent for Additive Nonparametric Regression. CoRR (2024)
Jianqing Fan, Cheng Gao, Jason M. Klusowski
Robust Transfer Learning with Unreliable Source Data. CoRR (2023)
Xin Chen, Jason M. Klusowski, Yan Shuo Tan
Error Reduction from Stacked Regressions. CoRR (2023)
Matias D. Cattaneo, Jason M. Klusowski, Boris Shigida
On the Implicit Bias of Adam. CoRR (2023)
Jason M. Klusowski, Jonathan W. Siegel
Sharp Convergence Rates for Matching Pursuit. CoRR (2023)
Matias D. Cattaneo, Jason M. Klusowski, Peter M. Tian
On the Pointwise Behavior of Recursive Partitioning and Its Implications for Heterogeneous Causal Effect Estimation. CoRR (2022)
Jason M. Klusowski
Sharp Analysis of a Simple Model for Random Forests. AISTATS (2021)
Jason M. Klusowski, Peter M. Tian
Nonparametric Variable Screening with Optimal Decision Stumps. AISTATS (2021)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. IEEE Trans. Inf. Theory 67 (1) (2021)
Jason M. Klusowski
Universal Consistency of Decision Trees for High Dimensional Additive Models. CoRR (2021)
Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney
Good Classifiers are Abundant in the Interpolating Regime. AISTATS (2021)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit. CoRR (2021)
Jason M. Klusowski
Sparse learning with CART. CoRR (2020)
Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney
Good linear classifiers are abundant in the interpolating regime. CoRR (2020)
Jason M. Klusowski, Peter M. Tian
Nonparametric Variable Screening with Optimal Decision Stumps. CoRR (2020)
Jason M. Klusowski
Sparse Learning with CART. NeurIPS (2020)
Jason M. Klusowski
Best Split Nodes for Regression Trees. CoRR (2019)
Jason M. Klusowski, Dana Yang, W. D. Brinda
Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization. IEEE Trans. Inf. Theory 65 (6) (2019)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. CoRR (2019)
Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. NeurIPS (2019)
Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher
Global Capacity Measures for Deep ReLU Networks via Path Sampling. CoRR (2019)
Andrew R. Barron, Jason M. Klusowski
Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation. CoRR (2019)
Jason M. Klusowski, Andrew R. Barron
Controls. IEEE Trans. Inf. Theory 64 (12) (2018)
Jason M. Klusowski, Yihong Wu
Estimating the Number of Connected Components in a Graph via Subgraph Sampling. CoRR (2018)
Jason M. Klusowski, Yihong Wu
Counting Motifs with Graph Sampling. COLT (2018)
Jason M. Klusowski, Yihong Wu
Counting Motifs with Graph Sampling. CoRR (2018)
Andrew R. Barron, Jason M. Klusowski
Approximation and Estimation for High-Dimensional Deep Learning Networks. CoRR (2018)
W. D. Brinda, Jason M. Klusowski
Finite-Sample Risk Bounds for Maximum Likelihood Estimation With Arbitrary Penalties. IEEE Trans. Inf. Theory 64 (4) (2018)
Jason M. Klusowski
Complete Analysis of a Random Forest Model. CoRR (2018)
Jason M. Klusowski, Andrew R. Barron
Minimax lower bounds for ridge combinations including neural nets. ISIT (2017)
Jason M. Klusowski, Andrew R. Barron
Minimax Lower Bounds for Ridge Combinations Including Neural Nets. CoRR (2017)