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Jason M. Klusowski
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2020 – today
- 2024
- [c8]Matias D. Cattaneo, Jason M. Klusowski, Boris Shigida:
On the Implicit Bias of Adam. ICML 2024 - [i23]Xin Chen, Jason M. Klusowski:
Stochastic Gradient Descent for Additive Nonparametric Regression. CoRR abs/2401.00691 (2024) - [i22]Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski:
Challenges in Variable Importance Ranking Under Correlation. CoRR abs/2402.03447 (2024) - [i21]Sijin Chen, Omar Hagrass, Jason M. Klusowski:
Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies. CoRR abs/2410.03968 (2024) - [i20]Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan:
Global Convergence in Training Large-Scale Transformers. CoRR abs/2410.23610 (2024) - 2023
- [i19]Jason M. Klusowski, Jonathan W. Siegel:
Sharp Convergence Rates for Matching Pursuit. CoRR abs/2307.07679 (2023) - [i18]Matias D. Cattaneo, Jason M. Klusowski, Boris Shigida:
On the Implicit Bias of Adam. CoRR abs/2309.00079 (2023) - [i17]Xin Chen, Jason M. Klusowski, Yan Shuo Tan:
Error Reduction from Stacked Regressions. CoRR abs/2309.09880 (2023) - [i16]Jianqing Fan, Cheng Gao, Jason M. Klusowski:
Robust Transfer Learning with Unreliable Source Data. CoRR abs/2310.04606 (2023) - 2022
- [i15]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 abs/2211.10805 (2022) - 2021
- [j4]Zhiqi Bu, Jason M. Klusowski
, Cynthia Rush
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. IEEE Trans. Inf. Theory 67(1): 506-537 (2021) - [c7]Jason M. Klusowski, Peter M. Tian:
Nonparametric Variable Screening with Optimal Decision Stumps. AISTATS 2021: 748-756 - [c6]Jason M. Klusowski:
Sharp Analysis of a Simple Model for Random Forests. AISTATS 2021: 757-765 - [c5]Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney:
Good Classifiers are Abundant in the Interpolating Regime. AISTATS 2021: 3376-3384 - [i14]Jason M. Klusowski:
Universal Consistency of Decision Trees for High Dimensional Additive Models. CoRR abs/2104.13881 (2021) - [i13]Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su:
Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit. CoRR abs/2105.13302 (2021) - 2020
- [c4]Jason M. Klusowski:
Sparse Learning with CART. NeurIPS 2020 - [i12]Jason M. Klusowski:
Sparse learning with CART. CoRR abs/2006.04266 (2020) - [i11]Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney:
Good linear classifiers are abundant in the interpolating regime. CoRR abs/2006.12625 (2020) - [i10]Jason M. Klusowski, Peter M. Tian:
Nonparametric Variable Screening with Optimal Decision Stumps. CoRR abs/2011.02683 (2020)
2010 – 2019
- 2019
- [j3]Jason M. Klusowski
Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization. IEEE Trans. Inf. Theory 65(6): 3515-3524 (2019) - [c3]Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su:
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. NeurIPS 2019: 9361-9371 - [i9]Andrew R. Barron, Jason M. Klusowski:
Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation. CoRR abs/1902.00800 (2019) - [i8]Jason M. Klusowski:
Best Split Nodes for Regression Trees. CoRR abs/1906.10086 (2019) - [i7]Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su:
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. CoRR abs/1907.07502 (2019) - [i6]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 abs/1910.10245 (2019) - 2018
- [j2]W. D. Brinda
Finite-Sample Risk Bounds for Maximum Likelihood Estimation With Arbitrary Penalties. IEEE Trans. Inf. Theory 64(4): 2727-2741 (2018) - [j1]Jason M. Klusowski
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With ℓ1 and ℓ0 Controls. IEEE Trans. Inf. Theory 64(12): 7649-7656 (2018) - [c2]Jason M. Klusowski, Yihong Wu:
Counting Motifs with Graph Sampling. COLT 2018: 1966-2011 - [i5]Jason M. Klusowski, Yihong Wu:
Estimating the Number of Connected Components in a Graph via Subgraph Sampling. CoRR abs/1801.04339 (2018) - [i4]Jason M. Klusowski, Yihong Wu:
Counting Motifs with Graph Sampling. CoRR abs/1802.07773 (2018) - [i3]Jason M. Klusowski:
Complete Analysis of a Random Forest Model. CoRR abs/1805.02587 (2018) - [i2]Andrew R. Barron, Jason M. Klusowski:
Approximation and Estimation for High-Dimensional Deep Learning Networks. CoRR abs/1809.03090 (2018) - 2017
- [c1]Jason M. Klusowski, Andrew R. Barron:
Minimax lower bounds for ridge combinations including neural nets. ISIT 2017: 1376-1380 - [i1]Jason M. Klusowski, Andrew R. Barron:
Minimax Lower Bounds for Ridge Combinations Including Neural Nets. CoRR abs/1702.02828 (2017)
Coauthor Index
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