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Harini Suresh
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2020 – today
- 2024
- [c14]Harini Suresh
, Emily Tseng
Participation in the age of foundation models. FAccT 2024: 1609-1621 - [i15]Harini Suresh, Emily Tseng, Meg Young, Mary L. Gray, Emma Pierson, Karen Levy:
Participation in the age of foundation models. CoRR abs/2405.19479 (2024) - 2023
- [b1]Harini Suresh:
Context and Participation in Machine Learning. MIT, USA, 2023 - [c13]Harini Suresh
Kaleidoscope: Semantically-grounded, context-specific ML model evaluation. CHI 2023: 775:1-775:13 - [c12]Angie W. Boggust
Saliency Cards: A Framework to Characterize and Compare Saliency Methods. FAccT 2023: 285-296 - [i14]Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy
Use large language models to promote equity. CoRR abs/2312.14804 (2023) - 2022
- [j4]Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23: 226:1-226:61 (2022) - [j3]Catherine D'Ignazio, Isadora Cruxên, Helena Suárez Val
Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence. Patterns 3(7): 100530 (2022) - [c11]William Boag, Harini Suresh, Bianca Lepe, Catherine D'Ignazio:
Tech Worker Organizing for Power and Accountability. FAccT 2022: 452-463 - [c10]Harini Suresh, Rajiv Movva, Amelia Lee Dogan
Towards Intersectional Feminist and Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection. FAccT 2022: 667-678 - [c9]Harini Suresh, Kathleen M. Lewis, John V. Guttag, Arvind Satyanarayan:
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs. IUI 2022: 767-781 - [i13]Angie W. Boggust, Harini Suresh, Hendrik Strobelt, John V. Guttag, Arvind Satyanarayan:
Beyond Faithfulness: A Framework to Characterize and Compare Saliency Methods. CoRR abs/2206.02958 (2022) - [i12]Helen Lu, Divya Shanmugam, Harini Suresh, John V. Guttag:
Improved Text Classification via Test-Time Augmentation. CoRR abs/2206.13607 (2022) - 2021
- [j2]Susanne Gaube
Do as AI say: susceptibility in deployment of clinical decision-aids. npj Digit. Medicine 4 (2021) - [c8]Harini Suresh, Steven R. Gomez, Kevin K. Nam, Arvind Satyanarayan
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs. CHI 2021: 74:1-74:16 - [c7]Harini Suresh, John V. Guttag:
A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle. EAAMO 2021: 17:1-17:9 - [i11]Harini Suresh, Steven R. Gomez, Kevin K. Nam, Arvind Satyanarayan:
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs. CoRR abs/2101.09824 (2021) - [i10]Harini Suresh, Kathleen M. Lewis, John V. Guttag, Arvind Satyanarayan:
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs. CoRR abs/2102.08540 (2021) - 2020
- [c6]Harini Suresh, Natalie Lao, Ilaria Liccardi:
Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making. WebSci 2020: 315-324 - [i9]Harini Suresh, Natalie Lao, Ilaria Liccardi:
Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making. CoRR abs/2005.10960 (2020) - [i8]Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR abs/2011.03395 (2020)
2010 – 2019
- 2019
- [i7]Harini Suresh, John V. Guttag:
A Framework for Understanding Unintended Consequences of Machine Learning. CoRR abs/1901.10002 (2019) - [i6]Ava P. Soleimany, Harini Suresh, Jose Javier Gonzalez Ortiz, Divya Shanmugam, Nil Gural, John V. Guttag, Sangeeta N. Bhatia:
Image segmentation of liver stage malaria infection with spatial uncertainty sampling. CoRR abs/1912.00262 (2019) - 2018
- [j1]Filipe Betzel
Approximate Communication: Techniques for Reducing Communication Bottlenecks in Large-Scale Parallel Systems. ACM Comput. Surv. 51(1): 1:1-1:32 (2018) - [c5]Matthew B. A. McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi:
Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. AAAI 2018: 2363-2370 - [c4]Harini Suresh, Jen J. Gong, John V. Guttag:
Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU. KDD 2018: 802-810 - [c3]Willie Boag, Harini Suresh, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Racial Disparities and Mistrust in End-of-Life Care. MLHC 2018: 587-602 - [i5]Harini Suresh, Jen J. Gong, John V. Guttag:
Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU. CoRR abs/1806.02878 (2018) - [i4]Willie Boag, Harini Suresh, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Modeling Mistrust in End-of-Life Care. CoRR abs/1807.00124 (2018) - 2017
- [c2]Harini Suresh, Shashank Hegde, John Sartori:
Approximate compression: enhancing compressibility through data approximation. ESTIMedia 2017: 41-50 - [c1]Harini Suresh, Nathan Hunt, Alistair E. W. Johnson, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Clinical Intervention Prediction and Understanding with Deep Neural Networks. MLHC 2017: 322-337 - [i3]Harini Suresh, Peter Szolovits, Marzyeh Ghassemi:
The Use of Autoencoders for Discovering Patient Phenotypes. CoRR abs/1703.07004 (2017) - [i2]Harini Suresh, Nathan Hunt, Alistair E. W. Johnson, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Clinical Intervention Prediction and Understanding using Deep Networks. CoRR abs/1705.08498 (2017) - 2015
- [i1]Harini Suresh, Nicholas Locascio:
Autodetection and Classification of Hidden Cultural City Districts from Yelp Reviews. CoRR abs/1501.02527 (2015)
Coauthor Index
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last updated on 2024-09-13 00:44 CEST by the dblp team
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