Bin YU
Bin YU
Professor of Statistics and EECS, UC Berkeley
Verified email at stat.berkeley.edu - Homepage
Title
Cited by
Year
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods
A Agarwal, YS Tan, O Ronen, C Singh, B Yu
arXiv preprint arXiv:2202.00858, 2022
12022
Fast interpretable greedy-tree sums (FIGS)
YS Tan, C Singh, K Nasseri, A Agarwal, B Yu
arXiv preprint arXiv:2201.11931, 2022
22022
VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS
J Duncan, R Kapoor, A Agarwal, C Singh, B Yu
Journal of Open Source Software 7 (69), 3895, 2022
2022
Predictability and Stability Testing to Assess Clinical Decision Instrument Performance for Children After Blunt Torso Trauma
AE Kornblith, C Singh, G Devlin, N Addo, CJ Streck, JF Holmes, ...
medRxiv, 2022
2022
Fast Interpretable Greedy-Tree Sums (FIGS)
Y Shuo Tan, C Singh, K Nasseri, A Agarwal, B Yu
arXiv e-prints, arXiv: 2201.11931, 2022
2022
Interpreting and improving deep-learning models with reality checks
C Singh, W Ha, B Yu
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2022
2022
Adaptive wavelet distillation from neural networks through interpretations
W Ha, C Singh, F Lanusse, S Upadhyayula, B Yu
Advances in Neural Information Processing Systems 34, 2021
62021
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
YS Tan, A Agarwal, B Yu
arXiv preprint arXiv:2110.09626, 2021
12021
Towards Robust Waveform-Based Acoustic Models
D Oglic, Z Cvetkovic, P Sollich, S Renals, B Yu
arXiv preprint arXiv:2110.08634, 2021
2021
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Y Shuo Tan, A Agarwal, B Yu
arXiv e-prints, arXiv: 2110.09626, 2021
2021
Supervised line attention for tumor attribute classification from pathology reports: Higher performance with less data
N Altieri, B Park, M Olson, J DeNero, AY Odisho, B Yu
Journal of Biomedical Informatics 122, 103872, 2021
12021
Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting
B Yu, C Singh
arXiv preprint arXiv:2108.08445, 2021
2021
Improving natural language information extraction from cancer pathology reports using transfer learning and zero-shot string similarity
B Park, N Altieri, J DeNero, AY Odisho, B Yu
JAMIA open 4 (3), ooab085, 2021
2021
imodels: a python package for fitting interpretable models
C Singh, K Nasseri, YS Tan, T Tang, B Yu
Journal of Open Source Software 6 (61), 3192, 2021
62021
iRF v2. 0
JB Brown, S Basu, K Kumbier, B Yu
Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States); Univ …, 2021
2021
Provable Boolean Interaction Recovery from Tree Ensemble obtained via Random Forests
M Behr, Y Wang, X Li, B Yu
arXiv preprint arXiv:2102.11800, 2021
12021
Structural Compression of Convolutional Neural Networks with Applications in Interpretability
R Abbasi-Asl, B Yu
Frontiers in big Data 4, 2021
22021
Independence and Diversity as Taught by My Mentors
B Yu
Leadership in Statistics and Data Science, 341-348, 2021
2021
Enriched Annotations for Tumor Attribute Classification from Pathology Reports with Limited Labeled Data
N Altieri, B Park, M Olson, J DeNero, A Odisho, B Yu
arXiv preprint arXiv:2012.08113, 2020
2020
Stable discovery of interpretable subgroups via calibration in causal studies
R Dwivedi, YS Tan, B Park, M Wei, K Horgan, D Madigan, B Yu
International Statistical Review 88, S135-S178, 2020
82020
The system can't perform the operation now. Try again later.
Articles 1–20