4 citations · 6 across the 4 of their papers we have counts for
4 papers
Example-based Explanations for Random Forests using Machine Unlearning
Tanmay Surve, Romila Pradhan
Tree-based machine learning models, such as decision trees and random forests, have been hugely successful in classification tasks primarily because of their predictive power in su…
Counteracts: Testing Stereotypical Representation in Pre-trained Language Models
Damin Zhang, Julia Rayz, Romila Pradhan
Recently, language models have demonstrated strong performance on various natural language understanding tasks. Language models trained on large human-generated corpus encode not o…
Interpretable Data-Based Explanations for Fairness Debugging
Romila Pradhan, Jiongli Zhu, Boris Glavic +1
A wide variety of fairness metrics and eXplainable Artificial Intelligence (XAI) approaches have been proposed in the literature to identify bias in machine learning models that ar…
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra, Romila Pradhan, Babak Salimi
There has been a recent resurgence of interest in explainable artificial intelligence (XAI) that aims to reduce the opaqueness of AI-based decision-making systems, allowing humans…