Jason M. Klusowski

42 papers A* 6A 3B 1Journal 32

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Classification Imbalance as Transfer Learning. CoRR Eric Xia, Jason M. Klusowski
2025	J	`jnl`	Revisiting Randomization in Greedy Model Search. CoRR Xin Chen, Jason M. Klusowski, Yan Shuo Tan, Chang Yu
2025	J	`jnl`	Sharp Convergence Rates for Matching Pursuit. IEEE Trans. Inf. Theory Jason M. Klusowski, Jonathan W. Siegel
2024	J	`jnl`	Challenges in Variable Importance Ranking Under Correlation. CoRR Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik, Lingkang Huang, Richard Baumgartner, Jason M. Klusowski
2024	J	`jnl`	Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies. CoRR Sijin Chen, Omar Hagrass, Jason M. Klusowski
2024	A*	`conf`	Global Convergence in Training Large-Scale Transformers. NeurIPS Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan
2024	J	`jnl`	Global Convergence in Training Large-Scale Transformers. CoRR Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan
2024	A*	`conf`	On the Implicit Bias of Adam. ICML Matias D. Cattaneo, Jason M. Klusowski, Boris Shigida
2024	A*	`conf`	One-Layer Transformer Provably Learns One-Nearest Neighbor In Context. NeurIPS Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang
2024	J	`jnl`	One-Layer Transformer Provably Learns One-Nearest Neighbor In Context. CoRR Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang
2024	J	`jnl`	Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators. CoRR Yan Shuo Tan, Jason M. Klusowski, Krishnakumar Balasubramanian
2024	J	`jnl`	Stochastic Gradient Descent for Additive Nonparametric Regression. CoRR Xin Chen, Jason M. Klusowski
2023	J	`jnl`	Error Reduction from Stacked Regressions. CoRR Xin Chen, Jason M. Klusowski, Yan Shuo Tan
2023	J	`jnl`	On the Implicit Bias of Adam. CoRR Matias D. Cattaneo, Jason M. Klusowski, Boris Shigida
2023	J	`jnl`	Robust Transfer Learning with Unreliable Source Data. CoRR Jianqing Fan, Cheng Gao, Jason M. Klusowski
2023	J	`jnl`	Sharp Convergence Rates for Matching Pursuit. CoRR Jason M. Klusowski, Jonathan W. Siegel
2022	J	`jnl`	On the Pointwise Behavior of Recursive Partitioning and Its Implications for Heterogeneous Causal Effect Estimation. CoRR Matias D. Cattaneo, Jason M. Klusowski, Peter M. Tian
2021	J	`jnl`	Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. IEEE Trans. Inf. Theory Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
2021	J	`jnl`	Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit. CoRR Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
2021	A	`conf`	Good Classifiers are Abundant in the Interpolating Regime. AISTATS Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney
2021	A	`conf`	Nonparametric Variable Screening with Optimal Decision Stumps. AISTATS Jason M. Klusowski, Peter M. Tian
2021	A	`conf`	Sharp Analysis of a Simple Model for Random Forests. AISTATS Jason M. Klusowski
2021	J	`jnl`	Universal Consistency of Decision Trees for High Dimensional Additive Models. CoRR Jason M. Klusowski
2020	J	`jnl`	Good linear classifiers are abundant in the interpolating regime. CoRR Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney
2020	J	`jnl`	Nonparametric Variable Screening with Optimal Decision Stumps. CoRR Jason M. Klusowski, Peter M. Tian
2020	A*	`conf`	Sparse Learning with CART. NeurIPS Jason M. Klusowski
2020	J	`jnl`	Sparse learning with CART. CoRR Jason M. Klusowski
2019	A*	`conf`	Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. NeurIPS Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
2019	J	`jnl`	Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing. CoRR Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su
2019	J	`jnl`	Best Split Nodes for Regression Trees. CoRR Jason M. Klusowski
2019	J	`jnl`	Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation. CoRR Andrew R. Barron, Jason M. Klusowski
2019	J	`jnl`	Estimating the Coefficients of a Mixture of Two Linear Regressions by Expectation Maximization. IEEE Trans. Inf. Theory Jason M. Klusowski, Dana Yang, W. D. Brinda
2019	J	`jnl`	Global Capacity Measures for Deep ReLU Networks via Path Sampling. CoRR Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher
2018	J	`jnl`	Approximation and Estimation for High-Dimensional Deep Learning Networks. CoRR Andrew R. Barron, Jason M. Klusowski
2018	J	`jnl`	Approximation by Combinations of ReLU and Squared ReLU Ridge Functions With ℓ IEEE Trans. Inf. Theory Jason M. Klusowski, Andrew R. Barron
2018	J	`jnl`	Complete Analysis of a Random Forest Model. CoRR Jason M. Klusowski
2018	A*	`conf`	Counting Motifs with Graph Sampling. COLT Jason M. Klusowski, Yihong Wu
2018	J	`jnl`	Counting Motifs with Graph Sampling. CoRR Jason M. Klusowski, Yihong Wu
2018	J	`jnl`	Estimating the Number of Connected Components in a Graph via Subgraph Sampling. CoRR Jason M. Klusowski, Yihong Wu
2018	J	`jnl`	Finite-Sample Risk Bounds for Maximum Likelihood Estimation With Arbitrary Penalties. IEEE Trans. Inf. Theory W. D. Brinda, Jason M. Klusowski
2017	J	`jnl`	Minimax Lower Bounds for Ridge Combinations Including Neural Nets. CoRR Jason M. Klusowski, Andrew R. Barron
2017	B	`conf`	Minimax lower bounds for ridge combinations including neural nets. ISIT Jason M. Klusowski, Andrew R. Barron