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Divya Shanmugam
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Journal Articles
- 2014
- [j1]Krishnan Balachandran, Divya Shanmugam:
Controllability of nonlinear implicit fractional integrodifferential systems. Int. J. Appl. Math. Comput. Sci. 24(4): 713-722 (2014)
Conference and Workshop Papers
- 2023
- [c7]Harini Suresh
, Divya Shanmugam
, Tiffany Chen
, Annie G. Bryan
, Alexander D'Amour
, John V. Guttag
, Arvind Satyanarayan
:
Kaleidoscope: Semantically-grounded, context-specific ML model evaluation. CHI 2023: 775:1-775:13 - [c6]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva
, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen:
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS 2023: 1-12 - [c5]Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson:
Coarse race data conceals disparities in clinical risk score performance. MLHC 2023: 443-472 - 2022
- [c4]Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz:
Data Augmentation for Electrocardiograms. CHIL 2022: 282-310 - [c3]Divya Shanmugam, Fernando Diaz, Samira Shabanian, Michèle Finck, Asia Biega:
Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization. FAccT 2022: 839-849 - 2021
- [c2]Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan
, John V. Guttag:
Better Aggregation in Test-Time Augmentation. ICCV 2021: 1194-1203 - 2019
- [c1]Divya Shanmugam, Davis W. Blalock, John V. Guttag:
Multiple Instance Learning for ECG Risk Stratification. MLHC 2019: 124-139
Editorship
- 2023
- [e1]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Tom Hartvigsen, Harvineet Singh:
Machine Learning for Health, ML4H@NeurIPS 2023, 10 December 2023, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 225, PMLR 2023 [contents]
Informal and Other Publications
- 2023
- [i12]Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson:
Coarse race data conceals disparities in clinical risk score performance. CoRR abs/2304.09270 (2023) - [i11]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Thomas Hartvigsen, Harvineet Singh:
Machine Learning for Health symposium 2023 - Findings track. CoRR abs/2312.00655 (2023) - [i10]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
, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa:
Use large language models to promote equity. CoRR abs/2312.14804 (2023) - 2022
- [i9]Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz:
Data Augmentation for Electrocardiograms. CoRR abs/2204.04360 (2022) - [i8]Helen Lu, Divya Shanmugam, Harini Suresh, John V. Guttag:
Improved Text Classification via Test-Time Augmentation. CoRR abs/2206.13607 (2022) - [i7]Divya Shanmugam, Katie Lewis, Jose Javier Gonzalez Ortiz, Agnieszka Kurant, John V. Guttag:
At the Intersection of Deep Learning and Conceptual Art: The End of Signature. CoRR abs/2207.04312 (2022) - 2021
- [i6]Divya Shanmugam, Samira Shabanian, Fernando Diaz, Michèle Finck, Asia Biega:
Learning to Limit Data Collection via Scaling Laws: Data Minimization Compliance in Practice. CoRR abs/2107.08096 (2021) - [i5]Divya Shanmugam, Emma Pierson:
Quantifying Inequality in Underreported Medical Conditions. CoRR abs/2110.04133 (2021) - 2020
- [i4]Roshni Sahoo, Divya Shanmugam, John V. Guttag:
Unsupervised Domain Adaptation in the Absence of Source Data. CoRR abs/2007.10233 (2020) - [i3]Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag:
When and Why Test-Time Augmentation Works. CoRR abs/2011.11156 (2020) - 2019
- [i2]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
- [i1]Divya Shanmugam, Davis W. Blalock, Jen J. Gong, John V. Guttag:
Multiple Instance Learning for ECG Risk Stratification. CoRR abs/1812.00475 (2018)
Coauthor Index
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