Research
Publications
(* indicates students)
50. On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling. [arXiv]
R. Tang* and Y. Yang
Journal of Machine Learning Research, 2024
49. Adaptivity of Diffusion Models to Manifold Structures. [pdf]
R. Tang* and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2024
48. Minimizing Convex Functionals over the Space of Probability Measures via KL Divergence Gradient Flow. [arXiv]
R. Yao*, L. Huang* and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2024
47. Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming.
Y. Zhuang*, X. Chen, Y. Yang and R. Y. Zhang
International Conference on Learning Representations (ICLR, Selected for Oral), 2024
46. Bayesian Model Selection via Mean-field Variational Approximation. [arXiv]
Y. Zhang* and Y. Yang
Journal of the Royal Statistical Society: Series B, 2024
45. Minimax Rate of Distribution Estimation on Unknown Submanifold under Adversarial Losses.
R. Tang* and Y. Yang
Annals of Statistics, 2023
44. Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data.
Y. Zhuang*, X. Chen and Y. Yang
International Conference on Machine Learning (ICML), 2023
43. A Gromov--Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening.
Y. Chen*, R. Yao*, Y. Yang and J. Chen
International Conference on Machine Learning (ICML), 2023
42. Model-based Statistical Depth with Applications to Functional Data
W. Zhao*, Z. Xu*, Y. Mu*, Y. Yang and W. Wu
Journal of Nonparametric Statistics, 2023
41. Gaussian Processes with Errors in Variables: Theory and Computation.
S. Zhou*, D. Pati, T. Wang*, Y. Yang and R. J. Carroll
Journal of Machine Learning Research, 2023
40. Statistical Inference via Conditional Bayesian Posteriors in High-Dimensional Linear Regression.
T. Wu*, N. Narisetty and Y. Yang
Electronic Journal of Statistics, 2023
39. Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks.
Y. Chen*, T. Xu*, D. Hakkani-Tur, D. Jin, Y. Yang, R. Zhu
Transactions on Machine Learning Research, 2023
38. Minimax Nonparametric Two-Sample Test under Adversarial Losses.
R. Tang* and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2023
37. Wasserstein K-means for Clustering Probability Distributions.
Y. Zhuang*, X. Chen and Y. Yang
Conference on Neural Information Processing Systems (NeurIPS), 2022
36. Learning Topic Models: Identifiability and Finite-Sample Analysis.
Y. Chen*, S. He*, Y. Yang and F. Liang
Journal of the American Statistical Association, 2022
35. Mean-Field Nonparametric Estimation of Interacting Particle Systems.
R. Yao*, X. Chen and Y. Yang
Conference on Learning Theory (COLT), 2022
34. Bayesian Inference for Risk Minimization via Exponentially Tilted Empirical Likelihood.
R. Tang* and Y. Yang
Journal of the Royal Statistical Society: Series B, 2022
33. Sketch-and-Lift: Scalable Subsampled Semidefinite Program for K-means Clustering.
Y. Zhuang*, X. Chen and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2022
32. Structured Variational Inference in Bayesian State-Space Models.
H. Wang*, A. Bhattacharya, D. Pati and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2022
31. High-Dimensional Linear Regression via Implicit Regularization.
P. Zhao*, Y. Yang and Q. He
Biometrika, 2022
30. Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences.
Y. Chen, Q. Zeng, D. Hakkani-Tur, D. Jin, H. Ji and Y. Yang
North American Chapter of the Association for Computational Linguistics (NAACL), 2022
29. Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystrom Method.
Y. Chen*, Q. Zeng*, H. Ji and Y. Yang
Conference on Neural Information Processing Systems (NeurIPS), 2021
28. Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual Linear Bandit.
K. Li*, Y. Yang and N. Narisetty
Electronic Journal of Statistics, 2021
27. On Empirical Bayes Variational Autoencoder: An Excess Risk Bound.
R. Tang* and Y. Yang
Conference on Learning Theory (COLT), 2021
26. Cutoff for Exact Recovery of Gaussian Mixture Models.
X. Chen and Y. Yang
IEEE Transactions on Information Theory, 2021
25. Distributed Estimation for Principal Component Analysis: an Enlarged Eigenspace Analysis.
X. Chen, J. Lee, H. Li* and Y. Yang
Journal of the American Statistical Association, 2021
24. Diffusion K-means Clustering on Manifolds: Provable Exact Recovery via Semidefinite Relaxations.
X. Chen and Y. Yang
Applied and Computational Harmonic Analysis, 2021
23. Hanson-Wright Inequality in Hilbert Spaces with Application to K-means Clustering for Non-Euclidean Data.
X. Chen and Y. Yang
Bernoulli, 2021
22. Nonparametric Testing under Randomized Sketching.
M. Liu, Z. Shang, Y. Yang and G. Cheng
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
21. Beyond Rebalancing: Crowd-Sourcing and Geo-Fencing for Shared-Mobility Systems.
Q. He, T. Nie, Y. Yang and Z. Shen
Production and Operations Management, 2021
20. Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression.
Y. Chen* and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2021
19. Fast Statistical Leverage Score Approximation in Kernel Ridge Regression.
Y. Chen* and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2021
18. α-variational Inference with Statistical Guarantees.
Y. Yang, A. Bhattacharya and D. Pati
Annals of Statistics, 2020
17. Computationally Efficient Bayesian Sequential Function Monitoring.
W. Shamp*, R. Varbanov*, E. Chicken, A. Linero and Y. Yang
Journal of Quality Technology, 2020
16. Non-asymptotic Analysis for Nonparametric Testing.
Y. Yang, Z. Shang and G. Cheng
Conference on Learning Theory (COLT), 2020
15. Bayesian Fractional Posteriors.
A. Bhattacharya, D. Pati and Y. Yang
Annals of Statistics, 2019
14. Smart Energy Storage Management via Information Systems Design.
Q. He, Y. Yang, Q. Bai and B. Zhang
Energy Economics, 2019
13. A Bayesian Approach to Sequential Monitoring of Nonlinear Profiles Using Wavelets.
R. Varbanov*, E. Chicken, A. Linero and Y. Yang
Quality and Reliability Engineering International, 2019
12. Communication-Efficient Distributed Statistical Inference.
M. I. Jordan, J. D. Lee and Y. Yang
Journal of the American Statistical Association, 2018
11. Bayesian Regression Tree Ensembles that Adapt to Smoothness and Sparsity.
A. R. Linero and Y. Yang
Journal of the Royal Statistical Society: Series B, 2018
10. On the Statistical Optimality of Variational Bayes.
D. Pati, A. Bhattacharya and Y. Yang
Artificial Intelligence and Statistics Conference (AISTATS), 2018
9. Joint Estimation of Quantile Planes over Arbitrary Predictor Spaces [R package]
Y. Yang and S. T. Tokdar
Journal of the American Statistical Association, 2017
8. Randomized Sketches for Kernels: Fast and Optimal Non-Parametric Regression.
Y. Yang, M. Pilanci and M. J. Wainwright
Annals of Statistics, 2017
7. Wavelet-Based Bayesian Profile Monitoring.
R. Varbanov*, E. Chicken, A. Linero and Y. Yang
Industrial and Systems Engineering Research Conference (ISERC), 2017
6. On the Computational Complexity of High-Dimensional Bayesian Variable Selection.
Y. Yang, M. J. Wainwright and M. I. Jordan
Annals of Statistics, 2016
5. Bayesian Manifold Regression.
Y. Yang and D. B. Dunson
Annals of Statistics, 2016
4. Bayesian Conditional Tensor Factorizations for High-Dimensional Classification [Matlab code]
Y. Yang and D. B. Dunson
Journal of the American Statistical Association, 2016
3. Minimax Optimal Nonparametric Regression in High Dimensions.
Y. Yang and S. T. Tokdar
Annals of Statistics, 2015
2. Bayesian Crack Detection in Ultra High Resolution Multimodal Images of Paintings.
B. Cornelis, Y. Yang, J. T. Vogelstein, A. Dooms, I. Daubechies and D. B. Dunson
International Conference on Digital Signal Processing (ICDSP), 2013
1. A Compact Neural Network for Training Support Vector Machines.
Y. Yang, Q. He and X. Hu
Neurocomputing, 2012