Model Agnostic Contrastive Explanations for Structured Data

31 May 2019

Karthikeyan Shanmugam

Ruchi Puri

FAtt

ArXiv PDF HTML

Papers citing "Model Agnostic Contrastive Explanations for Structured Data"

46 / 46 papers shown

Title
Perturbation-efficient Zeroth-order Optimization for Hardware-friendly On-device Training Qitao Tan Sung-En Chang Rui Xia Huidong Ji Chence Yang ... Zheng Zhan Zhou Zou Yufei Wang Jin Lu Geng Yuan 41 0 0 28 Apr 2025
CELL your Model: Contrastive Explanations for Large Language Models Ronny Luss Erik Miehling Amit Dhurandhar 47 0 0 17 Jun 2024
Comparison of decision trees with Local Interpretable Model-Agnostic Explanations (LIME) technique and multi-linear regression for explaining support vector regression model in terms of root mean square error (RMSE) values Amit Thombre FAtt 15 1 0 10 Apr 2024
Fully Zeroth-Order Bilevel Programming via Gaussian Smoothing Alireza Aghasi Saeed Ghadimi 41 2 0 29 Mar 2024
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark Yihua Zhang Pingzhi Li Junyuan Hong Jiaxiang Li Yimeng Zhang ... Wotao Yin Mingyi Hong Zhangyang Wang Sijia Liu Tianlong Chen 35 45 0 18 Feb 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification Amit Dhurandhar Swagatam Haldar Dennis L. Wei Karthikeyan N. Ramamurthy FAtt 40 2 0 17 Feb 2024
Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method Elissa Mhanna Mohamad Assaad 55 1 0 30 Jan 2024
Navigating the Structured What-If Spaces: Counterfactual Generation via Structured Diffusion Nishtha Madaan Srikanta J. Bedathur DiffM 38 0 0 21 Dec 2023
Explainable History Distillation by Marked Temporal Point Process Sishun Liu Ke Deng Yan Wang Xiuzhen Zhang 35 0 0 13 Nov 2023
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training Aochuan Chen Yimeng Zhang Jinghan Jia James Diffenderfer Jiancheng Liu Konstantinos Parasyris Yihua Zhang Zheng-Wei Zhang B. Kailkhura Sijia Liu 37 43 0 03 Oct 2023
CLIMAX: An exploration of Classifier-Based Contrastive Explanations Praharsh Nanavati Ranjitha Prasad 42 0 0 02 Jul 2023
CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing Flows Tri Dung Duong Qian Li Guandong Xu OOD 40 7 0 26 Mar 2023
Data-centric Artificial Intelligence: A Survey Daochen Zha Zaid Pervaiz Bhat Kwei-Herng Lai Fan Yang Zhimeng Jiang Shaochen Zhong Xia Hu 27 193 0 17 Mar 2023
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions Manish Nagireddy Moninder Singh Samuel C. Hoffman Evaline Ju Karthikeyan N. Ramamurthy Kush R. Varshney 32 1 0 17 Feb 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 44 3 0 07 Feb 2023
Sanity checks and improvements for patch visualisation in prototype-based image classification Romain Xu-Darme Georges Quénot Zakaria Chihani M. Rousset 12 3 0 20 Jan 2023
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions Julia El Zini Mohamad Mansour M. Awad 33 1 0 19 Jan 2023
A survey and taxonomy of loss functions in machine learning Lorenzo Ciampiconi A. Elwood Marco Leonardi A. Mohamed A. Rozza MU FaML 11 27 0 13 Jan 2023
An Empirical Evaluation of Zeroth-Order Optimization Methods on AI-driven Molecule Optimization Elvin Lo Pin-Yu Chen 42 0 0 27 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs Jing Ma Ruocheng Guo Saumitra Mishra Aidong Zhang Jundong Li CML OOD 40 54 0 16 Oct 2022
MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation Wenzhuo Yang Jia Li Caiming Xiong Guosheng Lin CML 35 13 0 31 May 2022
Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI Greta Warren Mark T. Keane R. Byrne CML 27 22 0 21 Apr 2022
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning Amit Dhurandhar Karthikeyan N. Ramamurthy Kartik Ahuja Vijay Arya FAtt 30 4 0 28 Jan 2022
Post-discovery Analysis of Anomalous Subsets I. Mulang' William Ogallo G. Tadesse Aisha Walcott-Bryant 29 1 0 23 Nov 2021
On Quantitative Evaluations of Counterfactuals Frederik Hvilshoj Alexandros Iosifidis Ira Assent 19 10 0 30 Oct 2021
Let the CAT out of the bag: Contrastive Attributed explanations for Text Saneem A. Chemmengath A. Azad Ronny Luss Amit Dhurandhar FAtt 34 10 0 16 Sep 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White Willie Neiswanger 37 65 0 23 Jun 2021
Amortized Generation of Sequential Algorithmic Recourses for Black-box Models Sahil Verma Keegan E. Hines John P. Dickerson 22 23 0 07 Jun 2021
Causality-based Counterfactual Explanation for Classification Models Tri Dung Duong Qian Li Guandong Xu CML 11 1 0 03 May 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations Dieter Brughmans Pieter Leyman David Martens 35 63 0 15 Apr 2021
Contrastive Explanations for Explaining Model Adaptations André Artelt Fabian Hinder Valerie Vaquet Robert Feldhans Barbara Hammer 54 4 0 06 Apr 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 25 108 0 26 Feb 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 27 146 0 26 Feb 2021
Why model why? Assessing the strengths and limitations of LIME Jurgen Dieber S. Kirrane FAtt 26 97 0 30 Nov 2020
Contrastive Graph Neural Network Explanation Lukas Faber A. K. Moghaddam Roger Wattenhofer 31 36 0 26 Oct 2020
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 26 164 0 20 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 14 172 0 08 Oct 2020
Efficient computation of contrastive explanations André Artelt Barbara Hammer 11 9 0 06 Oct 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 27 19 0 26 Jun 2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning Sijia Liu Pin-Yu Chen B. Kailkhura Gaoyuan Zhang A. Hero III P. Varshney 26 224 0 11 Jun 2020
Multi-Objective Counterfactual Explanations Susanne Dandl Christoph Molnar Martin Binder B. Bischl 24 252 0 23 Apr 2020
Explaining Groups of Points in Low-Dimensional Representations Gregory Plumb Jonathan Terhorst S. Sankararaman Ameet Talwalkar 10 30 0 03 Mar 2020
Learning Global Transparent Models Consistent with Local Contrastive Explanations Tejaswini Pedapati Avinash Balakrishnan Karthikeyan Shanmugam Amit Dhurandhar FAtt 22 0 0 19 Feb 2020
An explanation method for Siamese neural networks Lev V. Utkin M. Kovalev E. Kasimov 27 14 0 18 Nov 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 29 380 0 03 Jul 2019
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017