Please see my Google Scholar profile for a complete list of publications and citation metrics.
Domain Adaptation meets Individual Fairness. And they get along.
D Mukherjee, F Petersen, M Yurochkin, Y Sun.
A linear adjustment based approach to posterior drift in transfer learning
S Maity, D Dutta, J Terhorst, Y Sun, M Banerjee.
Minimax optimal approaches to the label shift problem
S Maity, Y Sun, M Banerjee.
Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions
S Maity, Y Sun, M Banerjee. Journal of Machine Learning Research (2022+).
Matrix Completion Methods for the Total Electron Content Video Reconstruction
H Sun, Z Hua, J Ren, S Zou, Y Sun, Y Chen. Annals of Applied Statistics (2022+).
Uniform bounds for invariant subspace perturbations
A Damle, Y Sun. SIAM Journal of Matrix Analysis and Applications (2020).
Statistical convergence of the EM algorithm on Gaussian mixture models
R Zhao, Y Li, Y Sun. Electronic Journal of Statistics (2020).
A geometric approach to archetypal analysis and nonnegative matrix factorization
A Damle, Y Sun. Technometrics (2017).
2017 Technometrics Prize
Communication-efficient sparse regression
JD Lee, Q Liu, Y Sun, JE Taylor. Journal of Machine Learning Research (2017).
Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data
L Yang, J Tan, EJ O’Brien, … Y Sun, MA Saunders, BO Palsson. Proceedings of the National Academy of Sciences (2015).
On model selection consistency of regularized M-estimators
JD Lee, Y Sun, JE Taylor. Electronic Journal of Statistics (2015).
A short version appeared at NIPS 2013.
Proximal Newton-type methods for minimizing composite functions
JD Lee, Y Sun, MA Saunders. SIAM Journal on Optimization (2014).
A short version appeared at NIPS 2012.
Robust flux balance analysis of multiscale biochemical reaction networks
Y Sun, RMT Fleming, I Thiele, MA Saunders. BMC Bioinformatics (2013).
Post-processing for Individual Fairness
F Petersen, D Mukherjee, Y Sun, M Yurochkin. NeurIPS 2021.
On sensitivity of meta-learning to support data
M Agarwal, M Yurochkin, Y Sun. NeurIPS 2021.
Does enforcing fairness mitigate biases caused by subpopulation shift
S Maity, D Mukherjee, M Yurochkin, Y Sun. NeurIPS 2021.
Outlier-Robust Optimal Transport
D Mukherjee, A Guha, J Solomon, Y Sun, M Yurochkin. ICML 2021.
Statistical Inference for Individual Fairness
S Maity, S Xue, M Yurochkin, Y Sun. ICLR 2021.
Individually Fair Rankings
A Bower, H Eftekhari, M Yurochkin, Y Sun. ICLR 2021.
Individually fair gradient boosting
A Vargo, F Zhang, M Yurochkin, Y Sun. ICLR 2021.
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
M Yurochkin, Y Sun. ICLR 2021.
Two simple ways to learn individual fairness metrics from data
D Mukherjee, M Yurochkin, M Banerjee, Y Sun. ICML 2020.
Auditing ML models for individual bias and unfairness
S Xue, M Yurochkin, Y Sun. AISTATS 2020.
Training individually fair machine learning models with Sensitive Subspace Robustness
M Yurochkin, A Bower, Y Sun. ICLR 2020.
Precision Matrix Estimation with Noisy and Missing Data
R Fan, B Jang, Y Sun, S Zhou. AISTATS 2019.
Debiasing representations by removing unwanted variation due to protected attributes
A Bower, L Niss, Y Sun, A Vargo. FAT/ML 2018.
Feature-distributed sparse regression: a screen-and-clean approach
J Yang, MW Mahoney, M Saunders, Y Sun. NIPS 2016.
Evaluating the statistical significance of biclusters
JD Lee, Y Sun, JE Taylor. NIPS 2015.
Learning Mixtures of Linear Classifiers
Y Sun, S Ioannidis, A Montanari. ICML 2014.
Achieving Representative Data via Convex Hull Feasibility Sampling Algorithms
L Niss, Y Sun, A Tewari.
On conditional parity as a notion of non-discrimination in machine learning
Y Ritov, Y Sun, R Zhao.
An inexact subsampled proximal Newton-type method for large-scale machine learning
X Liu, CJ Hsieh, JD Lee, Y Sun.
Valid post-correction inference for censored regression problems
Y Sun, JE Taylor.