Yuekai Sun

According to our database1, Yuekai Sun authored at least 38 papers between 2012 and 2022.

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Bibliography

2022
How does overparametrization affect performance on minority groups?
CoRR, 2022

Understanding new tasks through the lens of training data via exponential tilting.
CoRR, 2022

Predictor-corrector algorithms for stochastic optimization under gradual distribution shift.
CoRR, 2022

Domain Adaptation meets Individual Fairness. And they get along.
CoRR, 2022

Achieving Representative Data via Convex Hull Feasibility Sampling Algorithms.
CoRR, 2022

2021
Individually Fair Ranking.
CoRR, 2021

Post-processing for Individual Fairness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Does enforcing fairness mitigate biases caused by subpopulation shift?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On sensitivity of meta-learning to support data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Outlier-Robust Optimal Transport.
Proceedings of the 38th International Conference on Machine Learning, 2021

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness.
Proceedings of the 9th International Conference on Learning Representations, 2021

Individually Fair Gradient Boosting.
Proceedings of the 9th International Conference on Learning Representations, 2021

Statistical inference for individual fairness.
Proceedings of the 9th International Conference on Learning Representations, 2021

Individually Fair Rankings.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Uniform Bounds for Invariant Subspace Perturbations.
SIAM J. Matrix Anal. Appl., 2020

There is no trade-off: enforcing fairness can improve accuracy.
CoRR, 2020

Two Simple Ways to Learn Individual Fairness Metrics from Data.
Proceedings of the 37th International Conference on Machine Learning, 2020

Training individually fair ML models with sensitive subspace robustness.
Proceedings of the 8th International Conference on Learning Representations, 2020

Federated Learning with Matched Averaging.
Proceedings of the 8th International Conference on Learning Representations, 2020

Auditing ML Models for Individual Bias and Unfairness.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Learning fair predictors with Sensitive Subspace Robustness.
CoRR, 2019

Dirichlet Simplex Nest and Geometric Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Precision Matrix Estimation with Noisy and Missing Data.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Debiasing representations by removing unwanted variation due to protected attributes.
CoRR, 2018

2017
A Geometric Approach to Archetypal Analysis and Nonnegative Matrix Factorization.
Technometrics, 2017

Communication-efficient Sparse Regression.
J. Mach. Learn. Res., 2017

An inexact subsampled proximal Newton-type method for large-scale machine learning.
CoRR, 2017

On conditional parity as a notion of non-discrimination in machine learning.
CoRR, 2017

2016
Feature-distributed sparse regression: a screen-and-clean approach.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Communication-efficient sparse regression: a one-shot approach.
CoRR, 2015

Evaluating the statistical significance of biclusters.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Proximal Newton-Type Methods for Minimizing Composite Functions.
SIAM J. Optim., 2014

Learning Mixtures of Linear Classifiers.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
On model selection consistency of regularized M-estimators.
CoRR, 2013

Robust flux balance analysis of multiscale biochemical reaction networks.
BMC Bioinform., 2013

On model selection consistency of penalized M-estimators: a geometric theory.
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

2012
Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form
CoRR, 2012

Proximal Newton-type methods for convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012


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