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ORCIDYan Shuo Tan
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2020 – today
- 2024
[i16]Yan Shuo Tan, Omer Ronen, Theo Saarinen, Bin Yu:
The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis. CoRR abs/2406.19958 (2024)- [i15]Jean Feng, Avni Kothari, Luke Zier, Chandan Singh, Yan Shuo Tan:
Bayesian Concept Bottleneck Models with LLM Priors. CoRR abs/2410.15555 (2024) - [i14]Yan Shuo Tan, Jason M. Klusowski, Krishnakumar Balasubramanian:
Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators. CoRR abs/2411.04394 (2024) - 2023
- [j2]Yan Shuo Tan, Roman Vershynin:
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval. J. Mach. Learn. Res. 24: 58:1-58:47 (2023) - [i13]Abhineet Agarwal, Ana M. Kenney, Yan Shuo Tan, Tiffany M. Tang, Bin Yu:
MDI+: A Flexible Random Forest-Based Feature Importance Framework. CoRR abs/2307.01932 (2023) - [i12]Xin Chen, Jason M. Klusowski, Yan Shuo Tan:
Error Reduction from Stacked Regressions. CoRR abs/2309.09880 (2023) - 2022
- [c3]Yan Shuo Tan, Abhineet Agarwal, Bin Yu:
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds. AISTATS 2022: 9663-9685 - [c2]Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu:
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models. ICML 2022: 111-135 - [i11]Yan Shuo Tan, Chandan Singh, Keyan Nasseri, Abhineet Agarwal, Bin Yu:
Fast Interpretable Greedy-Tree Sums (FIGS). CoRR abs/2201.11931 (2022) - [i10]Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu:
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods. CoRR abs/2202.00858 (2022) - [i9]Omer Ronen, Theo Saarinen, Yan Shuo Tan, James Duncan, Bin Yu:
A Mixing Time Lower Bound for a Simplified Version of BART. CoRR abs/2210.09352 (2022) - 2021
- [j1]Chandan Singh
, Keyan Nasseri, Yan Shuo Tan, Tiffany M. Tang, Bin Yu:
imodels: a python package for fitting interpretable models. J. Open Source Softw. 6(61): 3192 (2021) - [i8]Yan Shuo Tan, Abhineet Agarwal, Bin Yu:
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds. CoRR abs/2110.09626 (2021) - 2020
- [i7]Nick Altieri, Rebecca L. Barter, James Duncan, Raaz Dwivedi, Karl Kumbier, Xiao Li, Robert Netzorg, Briton Park, Chandan Singh, Yan Shuo Tan, Tiffany M. Tang, Yu Wang, Bin Yu:
Curating a COVID-19 data repository and forecasting county-level death counts in the United States. CoRR abs/2005.07882 (2020) - [i6]Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu:
Stable discovery of interpretable subgroups via calibration in causal studies. CoRR abs/2008.10109 (2020)
2010 – 2019
- 2019
- [i5]Yan Shuo Tan, Roman Vershynin:
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval. CoRR abs/1910.12837 (2019) - 2018
- [c1]Yan Shuo Tan, Roman Vershynin:
Polynomial Time and Sample Complexity for Non-Gaussian Component Analysis: Spectral Methods. COLT 2018: 498-534 - 2017
- [i4]Yan Shuo Tan, Roman Vershynin:
Polynomial Time and Sample Complexity for Non-Gaussian Component Analysis: Spectral Methods. CoRR abs/1704.01041 (2017) - [i3]Yan Shuo Tan, Roman Vershynin:
Phase Retrieval via Randomized Kaczmarz: Theoretical Guarantees. CoRR abs/1706.09993 (2017) - [i2]Yan Shuo Tan:
Sparse Phase Retrieval via Sparse PCA Despite Model Misspecification: A Simplified and Extended Analysis. CoRR abs/1712.04106 (2017) - 2016
- [i1]Yan Shuo Tan:
Energy optimization for distributions on the sphere and improvement to the Welch bounds. CoRR abs/1612.06343 (2016)
Coauthor Index
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