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Ashia Wilson
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- affiliation: MIT, Cambridge, MA, USA
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Journal Articles
- 2021
- [j1]Ashia C. Wilson, Ben Recht, Michael I. Jordan:
A Lyapunov Analysis of Accelerated Methods in Optimization. J. Mach. Learn. Res. 22: 113:1-113:34 (2021)
Conference and Workshop Papers
- 2024
- [c15]Shomik Jain, Dana Calacci, Ashia Wilson:
As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making. AIES (1) 2024: 624-633 - [c14]Ishana Shastri, Shomik Jain, Barbara Engelhardt, Ashia Wilson:
Automating Transparency Mechanisms in the Judicial System Using LLMs: Opportunities and Challenges. AIES (1) 2024: 1357-1367 - [c13]Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson:
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm. COLT 2024: 4593-4635 - [c12]Shomik Jain, Vinith M. Suriyakumar, Kathleen Creel, Ashia Wilson:
Algorithmic Pluralism: A Structural Approach To Equal Opportunity. FAccT 2024: 197-206 - [c11]Qiang Fu, Ashia Camage Wilson:
Mean-field Underdamped Langevin Dynamics and its Spacetime Discretization. ICML 2024 - [c10]Shomik Jain, Kathleen Creel, Ashia Camage Wilson:
Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized. ICML 2024 - 2023
- [c9]Qiang Fu, Dongchu Xu, Ashia Camage Wilson:
Accelerated Stochastic Optimization Methods under Quasar-convexity. ICML 2023: 10431-10460 - 2022
- [c8]Simon Weissmann, Ashia Wilson, Jakob Zech:
Multilevel Optimization for Inverse Problems. COLT 2022: 5489-5524 - [c7]Vinith M. Suriyakumar, Ashia C. Wilson:
Algorithms that Approximate Data Removal: New Results and Limitations. NeurIPS 2022 - 2020
- [c6]Ashia C. Wilson, Maximilian Kasy, Lester Mackey:
Approximate Cross-validation: Guarantees for Model Assessment and Selection. AISTATS 2020: 4530-4540 - [c5]Lydia T. Liu, Ashia Wilson, Nika Haghtalab, Adam Tauman Kalai, Christian Borgs, Jennifer T. Chayes:
The disparate equilibria of algorithmic decision making when individuals invest rationally. FAT* 2020: 381-391 - 2019
- [c4]Ashia C. Wilson, Lester Mackey, Andre Wibisono:
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions. NeurIPS 2019: 13533-13543 - 2017
- [c3]Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht:
Breaking Locality Accelerates Block Gauss-Seidel. ICML 2017: 3482-3491 - [c2]Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nati Srebro, Benjamin Recht:
The Marginal Value of Adaptive Gradient Methods in Machine Learning. NIPS 2017: 4148-4158 - 2013
- [c1]Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan:
Streaming Variational Bayes. NIPS 2013: 1727-1735
Informal and Other Publications
- 2024
- [i17]Shomik Jain, Kathleen Creel, Ashia Wilson:
Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized. CoRR abs/2404.08592 (2024) - [i16]Shomik Jain, Dan Calacci, Ashia Wilson:
As an AI Language Model, "Yes I Would Recommend Calling the Police": Norm Inconsistency in LLM Decision-Making. CoRR abs/2405.14812 (2024) - [i15]Omri Lev, Ashia Wilson:
Faster Machine Unlearning via Natural Gradient Descent. CoRR abs/2407.08169 (2024) - [i14]Ishana Shastri, Shomik Jain, Barbara Engelhardt, Ashia Wilson:
Automating Transparency Mechanisms in the Judicial System Using LLMs: Opportunities and Challenges. CoRR abs/2408.08477 (2024) - [i13]Joao V. Cavalcanti, Laurent Lessard, Ashia C. Wilson:
Adaptive Backtracking For Faster Optimization. CoRR abs/2408.13150 (2024) - [i12]Vinith M. Suriyakumar, Rohan Alur, Ayush Sekhari, Manish Raghavan, Ashia C. Wilson:
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models. CoRR abs/2410.08074 (2024) - 2023
- [i11]Shomik Jain, Vinith M. Suriyakumar, Ashia Wilson:
Algorithmic Pluralism: A Structural Approach Towards Equal Opportunity. CoRR abs/2305.08157 (2023) - [i10]Zoe De Simone, Angie W. Boggust, Arvind Satyanarayan, Ashia Wilson:
What is a Fair Diffusion Model? Designing Generative Text-To-Image Models to Incorporate Various Worldviews. CoRR abs/2309.09944 (2023) - [i9]Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson:
Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin Algorithm. CoRR abs/2312.08823 (2023) - 2022
- [i8]Simon Weissmann, Ashia Wilson, Jakob Zech:
Multilevel Optimization for Inverse Problems. CoRR abs/2204.13732 (2022) - [i7]Vinith M. Suriyakumar, Ashia C. Wilson:
Algorithms that Approximate Data Removal: New Results and Limitations. CoRR abs/2209.12269 (2022) - 2020
- [i6]Ashia C. Wilson, Maximilian Kasy, Lester Mackey:
Approximate Cross-validation: Guarantees for Model Assessment and Selection. CoRR abs/2003.00617 (2020) - 2019
- [i5]Lydia T. Liu, Ashia Wilson, Nika Haghtalab, Adam Tauman Kalai, Christian Borgs, Jennifer T. Chayes:
The Disparate Equilibria of Algorithmic Decision Making when Individuals Invest Rationally. CoRR abs/1910.04123 (2019) - 2017
- [i4]Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nathan Srebro, Benjamin Recht:
The Marginal Value of Adaptive Gradient Methods in Machine Learning. CoRR abs/1705.08292 (2017) - 2016
- [i3]Andre Wibisono, Ashia C. Wilson, Michael I. Jordan:
A Variational Perspective on Accelerated Methods in Optimization. CoRR abs/1603.04245 (2016) - [i2]Ashia C. Wilson, Benjamin Recht, Michael I. Jordan:
A Lyapunov Analysis of Momentum Methods in Optimization. CoRR abs/1611.02635 (2016) - 2013
- [i1]Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan:
Streaming Variational Bayes. CoRR abs/1307.6769 (2013)
Coauthor Index
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