Accuracy, Interpretability, and Differential Privacy via Explainable Boosting

17 June 2021

Papers citing "Accuracy, Interpretability, and Differential Privacy via Explainable Boosting"

21 / 21 papers shown

Title
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review Sonal Allana Mohan Kankanhalli Rozita Dara 32 0 0 05 May 2025
GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Wenjie Kang L. Jiskoot Peter De Deyn G. Biessels Huiberdina Koek ... H. Middelkoop W. M. van der Flier Willemijn J. Jansen S. Klein Esther E. Bron 29 0 0 20 Jan 2025
Quantum Gradient Class Activation Map for Model Interpretability Hsin-Yi Lin Huan-Hsin Tseng Samuel Yen-Chi Chen Shinjae Yoo FAtt 31 5 0 12 Aug 2024
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability Fatima Ezzeddine Mirna Saad Omran Ayoub Davide Andreoletti M. Gjoreski Ihab Sbeity Marc Langheinrich Silvia Giordano 18 2 0 09 Apr 2024
Automation of Quantum Dot Measurement Analysis via Explainable Machine Learning Daniel Schug Tyler J. Kovach M. A. Wolfe Jared Benson Sanghyeok Park J. Dodson J. Corrigan M. A. Eriksson Justyna P. Zwolak 18 1 0 21 Feb 2024
The Computational Complexity of Concise Hypersphere Classification E. Eiben R. Ganian Iyad A. Kanj S. Ordyniak Stefan Szeider 37 1 0 12 Dec 2023
Classification with Partially Private Features Zeyu Shen A. Krishnaswamy Janardhan Kulkarni Kamesh Munagala 31 4 0 11 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 47 2 0 07 Dec 2023
Interpretable Survival Analysis for Heart Failure Risk Prediction Mike Van Ness Tomas M. Bosschieter Natasha Din Andrew P Ambrosy Alexander Sandhu Madeleine Udell 17 4 0 24 Oct 2023
Causal Inference with Differentially Private (Clustered) Outcomes Adel Javanmard Vahab Mirrokni Jean Pouget-Abadie 27 2 0 02 Aug 2023
An explainable model to support the decision about the therapy protocol for AML J. Almeida Giovanna A. Castro J. Machado-Neto Tiago A. Almeida 6 1 0 05 Jul 2023
Improved Differentially Private Regression via Gradient Boosting Shuai Tang Sergul Aydore Michael Kearns Saeyoung Rho Aaron Roth Yichen Wang Yu-Xiang Wang Zhiwei Steven Wu FedML 32 4 0 06 Mar 2023
Smoothly Giving up: Robustness for Simple Models Tyler Sypherd Nathan Stromberg Richard Nock Visar Berisha Lalitha Sankar 18 1 0 17 Feb 2023
Estimate Deformation Capacity of Non-Ductile RC Shear Walls using Explainable Boosting Machine Z. Deger Gülsen Taskin Kaya J. Wallace 11 3 0 11 Jan 2023
Differentially Private Optimizers Can Learn Adversarially Robust Models Yuan Zhang Zhiqi Bu 16 3 0 16 Nov 2022
Federated Boosted Decision Trees with Differential Privacy Samuel Maddock Graham Cormode Tianhao Wang Carsten Maple S. Jha FedML 21 29 0 06 Oct 2022
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization Zijie J. Wang Chudi Zhong Rui Xin Takuya Takagi Zhi Chen Duen Horng Chau Cynthia Rudin Margo Seltzer 33 14 0 19 Sep 2022
Spending Privacy Budget Fairly and Wisely Lucas Rosenblatt Joshua Allen Julia Stoyanovich 29 4 0 27 Apr 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 17 13 0 22 Feb 2022
Attention-like feature explanation for tabular data A. Konstantinov Lev V. Utkin FAtt 21 5 0 10 Aug 2021
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction Caroline Linjun Wang Bin Han Bhrij Patel Cynthia Rudin FaML HAI 59 84 0 08 May 2020