Divya Shanmugam

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 19

Top Topics

Uncertainty Sampling

Data Collection

Image Categorization

Multiple Instance

Top Venues

Publications

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 (2023)
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 (2023)
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)
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 (2023)
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)
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)
Divya Shanmugam, Fernando Diaz, Samira Shabanian, Michele Finck, Asia Biega
Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization. FAccT (2022)
Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz
Data Augmentation for Electrocardiograms. CHIL (2022)
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 (2022)
Helen Lu, Divya Shanmugam, Harini Suresh, John V. Guttag
Improved Text Classification via Test-Time Augmentation. CoRR (2022)
Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz
Data Augmentation for Electrocardiograms. CoRR (2022)
Divya Shanmugam, Emma Pierson
Quantifying Inequality in Underreported Medical Conditions. CoRR (2021)
Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag
Better Aggregation in Test-Time Augmentation. ICCV (2021)
Divya Shanmugam, Samira Shabanian, Fernando Diaz, Michèle Finck, Asia Biega
Learning to Limit Data Collection via Scaling Laws: Data Minimization Compliance in Practice. CoRR (2021)
Roshni Sahoo, Divya Shanmugam, John V. Guttag
Unsupervised Domain Adaptation in the Absence of Source Data. CoRR (2020)
Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag
When and Why Test-Time Augmentation Works. CoRR (2020)
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 (2019)
Divya Shanmugam, Davis W. Blalock, John V. Guttag
Multiple Instance Learning for ECG Risk Stratification. MLHC (2019)
Divya Shanmugam, Davis W. Blalock, Jen J. Gong, John V. Guttag
Multiple Instance Learning for ECG Risk Stratification. CoRR (2018)