Harini Suresh

Orcid: 0000-0002-9769-4947

According to our database1, Harini Suresh authored at least 26 papers between 2015 and 2023.

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Bibliography

2023
Use large language models to promote equity.
CoRR, 2023

Saliency Cards: A Framework to Characterize and Compare Saliency Methods.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Kaleidoscope: Semantically-grounded, context-specific ML model evaluation.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022
Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence.
Patterns, 2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.
J. Mach. Learn. Res., 2022

Improved Text Classification via Test-Time Augmentation.
CoRR, 2022

Beyond Faithfulness: A Framework to Characterize and Compare Saliency Methods.
CoRR, 2022

Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs.
Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22, 2022

Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Tech Worker Organizing for Power and Accountability.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Do as AI say: susceptibility in deployment of clinical decision-aids.
npj Digit. Medicine, 2021

A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle.
Proceedings of the EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5, 2021

Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

2020
Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making.
Proceedings of the WebSci '20: 12th ACM Conference on Web Science, 2020

2019
Image segmentation of liver stage malaria infection with spatial uncertainty sampling.
CoRR, 2019

A Framework for Understanding Unintended Consequences of Machine Learning.
CoRR, 2019

2018
Approximate Communication: Techniques for Reducing Communication Bottlenecks in Large-Scale Parallel Systems.
ACM Comput. Surv., 2018

Modeling Mistrust in End-of-Life Care.
CoRR, 2018

Racial Disparities and Mistrust in End-of-Life Care.
Proceedings of the Machine Learning for Healthcare Conference, 2018

Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
The Use of Autoencoders for Discovering Patient Phenotypes.
CoRR, 2017

Clinical Intervention Prediction and Understanding using Deep Networks.
CoRR, 2017

Clinical Intervention Prediction and Understanding with Deep Neural Networks.
Proceedings of the Machine Learning for Health Care Conference, 2017

Approximate compression: enhancing compressibility through data approximation.
Proceedings of the 15th IEEE/ACM Symposium on Embedded Systems for Real-Time Multimedia, 2017

2015
Autodetection and Classification of Hidden Cultural City Districts from Yelp Reviews.
CoRR, 2015


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