Michael P. Kim

According to our database, Michael P. Kim authored at least 26 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Certifying Private Probabilistic Mechanisms.

Zoë Ruha Bell, Shafi Goldwasser, Michael P. Kim, Jean-Luc Watson

IACR Cryptol. ePrint Arch., 2024

2023

Characterizing notions of omniprediction via multicalibration.

Parikshit Gopalan, Michael P. Kim, Omer Reingold

CoRR, 2023

Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration.

Parikshit Gopalan, Michael P. Kim, Omer Reingold

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Making Decisions Under Outcome Performativity.

Michael P. Kim, Juan C. Perdomo

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

Loss Minimization Through the Lens Of Outcome Indistinguishability.

Parikshit Gopalan, Lunjia Hu, Michael P. Kim, Omer Reingold, Udi Wieder

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

Is Your Model Predicting the Past?

Michael P. Kim, Moritz Hardt

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

2022

Backward baselines: Is your model predicting the past?

Moritz Hardt, Michael P. Kim

CoRR, 2022

Planting Undetectable Backdoors in Machine Learning Models.

Shafi Goldwasser, Michael P. Kim, Vinod Vaikuntanathan, Or Zamir

CoRR, 2022

Planting Undetectable Backdoors in Machine Learning Models : [Extended Abstract].

Shafi Goldwasser, Michael P. Kim, Vinod Vaikuntanathan, Or Zamir

Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Low-Degree Multicalibration.

Parikshit Gopalan, Michael P. Kim, Mihir Singhal, Shengjia Zhao

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Beyond Bernoulli: Generating Random Outcomes that cannot be Distinguished from Nature.

Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

mcboost: Multi-Calibration Boosting for R.

Florian Pfisterer, Christoph Kern, Susanne Dandl, Mathew Sun, Michael P. Kim, Bernd Bischl

Dataset, August, 2021

Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration.

Shengjia Zhao, Michael P. Kim, Roshni Sahoo, Tengyu Ma, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

A complexity-theoretic perspective on fairness.

Michael P. Kim

PhD thesis, 2020

Outcome Indistinguishability.

Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona

Electron. Colloquium Comput. Complex., 2020

Preference-Informed Fairness.

Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, Gal Yona

Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

A Distributional Framework For Data Valuation.

Amirata Ghorbani, Michael P. Kim, James Zou

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning from Outcomes: Evidence-Based Rankings.

Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona

Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

Tracking and Improving Information in the Service of Fairness.

Sumegha Garg, Michael P. Kim, Omer Reingold

Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

Multiaccuracy: Black-Box Post-Processing for Fairness in Classification.

Michael P. Kim, Amirata Ghorbani, James Y. Zou

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Fairness Through Computationally-Bounded Awareness.

Michael P. Kim, Omer Reingold, Guy N. Rothblum

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multicalibration: Calibration for the (Computationally-Identifiable) Masses.

Úrsula Hébert-Johnson, Michael P. Kim, Omer Reingold, Guy N. Rothblum

Proceedings of the 35th International Conference on Machine Learning, 2018

On Estimating Edit Distance: Alignment, Dimension Reduction, and Embeddings.

Moses Charikar, Ofir Geri, Michael P. Kim, William Kuszmaul

Proceedings of the 45th International Colloquium on Automata, Languages, and Programming, 2018

2017

Who Can Win a Single-Elimination Tournament?

Michael P. Kim, Warut Suksompong, Virginia Vassilevska Williams

SIAM J. Discret. Math., 2017

Calibration for the (Computationally-Identifiable) Masses.

Úrsula Hébert-Johnson, Michael P. Kim, Omer Reingold, Guy N. Rothblum

CoRR, 2017

2015

Fixing Tournaments for Kings, Chokers, and More.

Michael P. Kim, Virginia Vassilevska Williams

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015