📚 Papers

• ›

  Revisiting Prompt Engineering via Declarative Crowdsourcing

  Preprint

  Aditya G. Parameswaran, Shreya Shankar, Parth Asawa, Naman Jain, Yujie Wang

• ›

  Moving Fast with Broken Data: Automatic and Precise Data Validation for Machine Learning

  To appear at CIKM 2023

  Shreya Shankar, Labib Fawaz, Karl Gyllstrom, Aditya G. Parameswaran

• ›

  Operationalizing Machine Learning: An Interview Study

  Preprint

  Shreya Shankar*, Rolando Garcia*, Joseph M. Hellerstein, Aditya G. Parameswaran

• ›

  Towards Observability for Production Machine Learning Pipelines

  VLDB 2023

  Shreya Shankar, Aditya G. Parameswaran

• ›

  Bolt-on, Compact, and Rapid Program Slicing for Notebooks

  VLDB 2023

  Shreya Shankar*, Stephen Macke*, Sarah Chasins, Andrew Head, Aditya G. Parameswaran

• ›

  Rethinking Streaming Machine Learning Evaluation

  ICLR 2022: Workshop on ML Evaluation Standards

  Shreya Shankar, Bernease Herman, Aditya G. Parameswaran

• ›

  Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming

  NeurIPS 2020

  Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy R Bunel, Shreya Shankar, Jacob Steinhardt, Ian Goodfellow, Percy S Liang, Pushmeet Kohli

• ›

  Adversarial examples that fool both computer vision and time-limited humans

  NIPS 2018

  Gamalelden F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian Goodfellow, Jascha Sohl-Dickstein

• ›

  No classification without representation: Assessing geodiversity issues in open data sets for the developing world

  NIPS 2017: Workshop on Machine Learning for the Developing World

  Shreya Shankar, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, D. Sculley