Ashia Wilson

Orcid: 0000-0001-7072-2912

Affiliations:
  • MIT, Cambridge, MA, USA


According to our database1, Ashia Wilson authored at least 21 papers between 2013 and 2024.

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Bibliography

2024
Faster Machine Unlearning via Natural Gradient Descent.
CoRR, 2024

As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making.
CoRR, 2024

Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized.
CoRR, 2024

Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mean-field Underdamped Langevin Dynamics and its Spacetime Discretization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Algorithmic Pluralism: A Structural Approach To Equal Opportunity.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
What is a Fair Diffusion Model? Designing Generative Text-To-Image Models to Incorporate Various Worldviews.
CoRR, 2023

Algorithmic Pluralism: A Structural Approach Towards Equal Opportunity.
CoRR, 2023

Accelerated Stochastic Optimization Methods under Quasar-convexity.
Proceedings of the International Conference on Machine Learning, 2023

2022
Algorithms that Approximate Data Removal: New Results and Limitations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multilevel Optimization for Inverse Problems.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
A Lyapunov Analysis of Accelerated Methods in Optimization.
J. Mach. Learn. Res., 2021

2020
The disparate equilibria of algorithmic decision making when individuals invest rationally.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Approximate Cross-validation: Guarantees for Model Assessment and Selection.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Breaking Locality Accelerates Block Gauss-Seidel.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
A Lyapunov Analysis of Momentum Methods in Optimization.
CoRR, 2016

A Variational Perspective on Accelerated Methods in Optimization.
CoRR, 2016

2013
Streaming Variational Bayes.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013


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