Auditing Black-box Models for Indirect Influence

23 February 2016

Suresh Venkatasubramanian

TDI

MLAU

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Papers citing "Auditing Black-box Models for Indirect Influence"

49 / 49 papers shown

Title
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee Puheng Li James Zou Linjun Zhang FaML 98 4 0 13 Mar 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning Numair Sani Daniel Malinsky I. Shpitser CML 86 16 0 10 Jan 2025
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 47 0 0 29 Oct 2024
Evaluating and Mitigating Discrimination in Language Model Decisions Alex Tamkin Amanda Askell Liane Lovitt Esin Durmus Nicholas Joseph Shauna Kravec Karina Nguyen Jared Kaplan Deep Ganguli 38 68 0 06 Dec 2023
Auditing large language models: a three-layered approach Jakob Mokander Jonas Schuett Hannah Rose Kirk Luciano Floridi AILaw MLAU 52 196 0 16 Feb 2023
"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment Yaniv Yacoby Ben Green Christopher L. Griffin Finale Doshi Velez 21 16 0 11 May 2022
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning A. Feder Cooper Emanuel Moss Benjamin Laufer Helen Nissenbaum MLAU 32 85 0 10 Feb 2022
Modeling Implicit Bias with Fuzzy Cognitive Maps Gonzalo Nápoles Isel Grau Leonardo Concepción Lisa Koutsoviti Koumeri João Paulo Papa 18 26 0 23 Dec 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 357 0 04 Oct 2021
Longitudinal Distance: Towards Accountable Instance Attribution Rosina O. Weber Prateek Goel S. Amiri G. Simpson 16 0 0 23 Aug 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 197 0 12 Jul 2021
Cohort Shapley value for algorithmic fairness Masayoshi Mase Art B. Owen Benjamin B. Seiler 18 14 0 15 May 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 27 105 0 22 Mar 2021
Software-Supported Audits of Decision-Making Systems: Testing Google and Facebook's Political Advertising Policies J. N. Matias Austin Hounsel Nick Feamster MLAU 19 15 0 26 Feb 2021
Explaining Black-box Models for Biomedical Text Classification M. Moradi Matthias Samwald 41 21 0 20 Dec 2020
Self-Explaining Structures Improve NLP Models Zijun Sun Chun Fan Qinghong Han Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li MILM XAI LRM FAtt 46 38 0 03 Dec 2020
Explainable Predictive Process Monitoring Musabir Musabayli F. Maggi Williams Rizzi Josep Carmona Chiara Di Francescomarino 19 60 0 04 Aug 2020
Relative Feature Importance Gunnar Konig Christoph Molnar B. Bischl Moritz Grosse-Wentrup 32 48 0 16 Jul 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 25 85 0 23 Jun 2020
Model Explanations with Differential Privacy Neel Patel Reza Shokri Yair Zick SILM FedML 28 32 0 16 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 39 0 26 May 2020
An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges D. Charte F. Charte M. J. D. Jesus Francisco Herrera SSL OOD 27 51 0 21 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Addressing multiple metrics of group fairness in data-driven decision making M. Miron Songül Tolan Emilia Gómez Carlos Castillo FaML 19 8 0 10 Mar 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 43 301 0 08 Jan 2020
Leveraging Semi-Supervised Learning for Fairness using Neural Networks Vahid Noroozi S. Bahaadini Samira Sheikhi Nooshin Mojab Philip S. Yu 8 7 0 31 Dec 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 41 6,125 0 22 Oct 2019
Does Object Recognition Work for Everyone? Terrance Devries Ishan Misra Changhan Wang Laurens van der Maaten 45 262 0 06 Jun 2019
The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services Yuantian Miao Minhui Xue Chao Chen Lei Pan Jinchao Zhang Benjamin Zi Hao Zhao Dali Kaafar Yang Xiang 21 34 0 17 May 2019
Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model Tong Wang Qihang Lin 38 19 0 10 May 2019
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions Hao Wang Berk Ustun Flavio du Pin Calmon FaML 33 83 0 29 Jan 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 25 135 0 24 Jan 2019
The Price of Fair PCA: One Extra Dimension Samira Samadi U. Tantipongpipat Jamie Morgenstern Mohit Singh Santosh Vempala FaML 22 154 0 31 Oct 2018
Hunting for Discriminatory Proxies in Linear Regression Models Samuel Yeom Anupam Datta Matt Fredrikson 22 19 0 16 Oct 2018
Defining Locality for Surrogates in Post-hoc Interpretablity Thibault Laugel X. Renard Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki FAtt 15 80 0 19 Jun 2018
Understanding Community Structure in Layered Neural Networks C. Watanabe Kaoru Hiramatsu K. Kashino 19 22 0 13 Apr 2018
Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data P. Schratz Jannes Muenchow E. Iturritxa Jakob Richter A. Brenning 28 320 0 29 Mar 2018
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges Gabrielle Ras Marcel van Gerven W. Haselager XAI 17 217 0 20 Mar 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 23 636 0 13 Feb 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation Menaka Narayanan Emily Chen Jeffrey He Been Kim S. Gershman Finale Doshi-Velez FAtt XAI 41 241 0 02 Feb 2018
Inverse Classification for Comparison-based Interpretability in Machine Learning Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 21 100 0 22 Dec 2017
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 37 677 0 26 Nov 2017
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability Mike Wu M. C. Hughes S. Parbhoo Maurizio Zazzi Volker Roth Finale Doshi-Velez AI4CE 28 281 0 16 Nov 2017
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation S. Tan R. Caruana Giles Hooker Yin Lou MLAU 28 180 0 17 Oct 2017
A Convex Framework for Fair Regression R. Berk Hoda Heidari S. Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth FaML 23 341 0 07 Jun 2017
EVE: Explainable Vector Based Embedding Technique Using Wikipedia M. A. Qureshi Derek Greene 30 33 0 22 Feb 2017
A causal framework for discovering and removing direct and indirect discrimination Lu Zhang Yongkai Wu Xintao Wu CML 24 172 0 22 Nov 2016
Achieving non-discrimination in data release Lu Zhang Yongkai Wu Xintao Wu FaML 18 68 0 22 Nov 2016
Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models Julius Adebayo Lalana Kagal MLAU 12 65 0 15 Nov 2016