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Tengyuan Liang · SciRah

Researcher profile · Semantic Scholar

Tengyuan Liang

University of Chicago

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Tengyuan Liang — researcher profile on SciRah

h-index: 23
Works: 61
Citations: 2,674

Most-cited papers

Just Interpolate: Kernel "Ridgeless" Regression Can Generalize
Tengyuan Liang, A. Rakhlin
2018Annals of Statistics384 citations Open access
Semantic Scholar
Deep Neural Networks for Estimation and Inference: Application to Causal Effects and Other Semiparametric Estimands
M. Farrell, Tengyuan Liang, S. Misra
2018Econometrica276 citations Open access
Semantic Scholar
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks
Tengyuan Liang, T. Poggio, A. Rakhlin, James Stokes
2017International Conference on Artificial Intelligence and Statistics265 citations
Semantic Scholar
DEEP NEURAL NETWORKS FOR ESTIMATION AND INFERENCE
Tengyuan Liang, Max H. Farrell, Sanjog Misra
2020255 citations
Semantic Scholar
Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks
Tengyuan Liang, James Stokes
2018International Conference on Artificial Intelligence and Statistics230 citations
Semantic Scholar
How Well Generative Adversarial Networks Learn Distributions
Tengyuan Liang
2018Journal of machine learning research127 citations Open access
Semantic Scholar
On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels
Tengyuan Liang, A. Rakhlin, Xiyu Zhai
2019Annual Conference Computational Learning Theory125 citations
Semantic Scholar
Learning with Square Loss: Localization through Offset Rademacher Complexity
Tengyuan Liang, A. Rakhlin, Karthik Sridharan
2015Annual Conference Computational Learning Theory89 citations
Semantic Scholar
Law of log determinant of sample covariance matrix and optimal estimation of differential entropy for high-dimensional Gaussian distributions
T. Cai, Tengyuan Liang, Harrison H. Zhou
2013Journal of Multivariate Analysis84 citations Open access
Semantic Scholar
Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions
A. Belloni, Tengyuan Liang, Hariharan Narayanan, A. Rakhlin
2015Annual Conference Computational Learning Theory83 citations
Semantic Scholar
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers
Tengyuan Liang, P. Sur
2020Social Science Research Network75 citations Open access
Semantic Scholar
Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix
T. Cai, Tengyuan Liang, A. Rakhlin
201567 citations Open access
Semantic Scholar
On How Well Generative Adversarial Networks Learn Densities: Nonparametric and Parametric Results
Tengyuan Liang
2018arXiv.org48 citations
Semantic Scholar
Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits
Xialiang Dou, Tengyuan Liang
2019Journal of the American Statistical Association44 citations Open access
Semantic Scholar
How Well Can Generative Adversarial Networks (GAN) Learn Densities: A Nonparametric View
Tengyuan Liang
2017arXiv.org44 citations
Semantic Scholar
Deep learning for individual heterogeneity: an automatic inference framework
M. Farrell, Tengyuan Liang, S. Misra
202142 citations Open access
Semantic Scholar
Textual Factors: A Scalable, Interpretable, and Data-Driven Approach to Analyzing Unstructured Information
Lin William Cong, Tengyuan Liang, Xiao Zhang, Wu Zhu
2024Management Sciences36 citations Open access
Semantic Scholar
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability
Belinda Tzen, Tengyuan Liang, M. Raginsky
2018Annual Conference Computational Learning Theory35 citations
Semantic Scholar
Interpolating Classifiers Make Few Mistakes
Tengyuan Liang, B. Recht
2021Journal of machine learning research32 citations
Semantic Scholar
On the Risk of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels
Tengyuan Liang, A. Rakhlin, Xiyu Zhai
2019arXiv.org29 citations
Semantic Scholar
Geometric Inference for General High-Dimensional Linear Inverse Problems
T. Cai, Tengyuan Liang, A. Rakhlin
201428 citations Open access
Semantic Scholar
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
Satyen Kale, Zohar S. Karnin, Tengyuan Liang, Dávid Pál
2017International Conference on Machine Learning26 citations
Semantic Scholar
On Zeroth-Order Stochastic Convex Optimization via Random Walks
Tengyuan Liang, Hariharan Narayanan, A. Rakhlin
2014arXiv.org24 citations
Semantic Scholar
Statistical inference for the population landscape via moment‐adjusted stochastic gradients
Tengyuan Liang, Weijie Su
2017Journal of The Royal Statistical Society Series B-statistical Methodology23 citations Open access
Semantic Scholar
Inference via Message Passing on Partially Labeled Stochastic Block Models
T. Cai, Tengyuan Liang, A. Rakhlin
201622 citations
Semantic Scholar
Estimating Certain Integral Probability Metrics (IPMs) Is as Hard as Estimating under the IPMs
Tengyuan Liang
2019Social Science Research Network18 citations Open access
Semantic Scholar
On Detection and Structural Reconstruction of Small-World Random Networks
T. Cai, Tengyuan Liang, A. Rakhlin
2016IEEE Transactions on Network Science and Engineering18 citations Open access
Semantic Scholar
Randomization Inference when N Equals One
Tengyuan Liang, B. Recht
2023Biometrika17 citations Open access
Semantic Scholar
Reversible Gromov-Monge Sampler for Simulation-Based Inference
Y. Hur, Wenxuan Guo, Tengyuan Liang
2021SIAM Journal on Mathematics of Data Science15 citations Open access
Semantic Scholar
High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
Tengyuan Liang, Subhabrata Sen, P. Sur
2022Information and Inference A Journal of the IMA12 citations Open access
Semantic Scholar
Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks
Tengyuan Liang, Hai Tran-Bach
2020Journal of the American Statistical Association12 citations Open access
Semantic Scholar
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information
T. Cai, Tengyuan Liang, A. Rakhlin
2017Journal of machine learning research10 citations
Semantic Scholar
A Precise High-Dimensional Asymptotic Theory for Boosting and Min-L1-Norm Interpolated Classifiers
Tengyuan Liang, Pragya Sur
2020arXiv.org9 citations
Semantic Scholar
Analyzing Textual Information at Scale
Lin William Cong, Tengyuan Liang, Bao-Zhong Yang, Xiao Zhang
2019Information for Efficient Decision Making9 citations Open access
Semantic Scholar
Online Learning to Transport via the Minimal Selection Principle
Wenxuan Guo, YoonHaeng Hur, Tengyuan Liang, C. Ryan
2022Annual Conference Computational Learning Theory8 citations
Semantic Scholar
On the Minimax Optimality of Estimating the Wasserstein Metric
Tengyuan Liang
2019arXiv.org8 citations
Semantic Scholar
Geometrizing Local Rates of Convergence for Linear Inverse Problems
T. T. Cai, Tengyuan Liang, A. Rakhlin
20148 citations
Semantic Scholar
Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity
Tengyuan Liang, Kulunu Dharmakeerthi, Takuya Koriyama
2024Trans. Mach. Learn. Res.7 citations
Semantic Scholar
No-Regret Generative Modeling via Parabolic Monge-Ampère PDE
Nabarun Deb, Tengyuan Liang
2025arXiv.org6 citations
Semantic Scholar
Geometrizing Local Rates of Convergence for High-Dimensional Linear Inverse Problems
T. Cai, Tengyuan Liang, A. Rakhlin
20146 citations
Semantic Scholar
Distributional Shrinkage I: Universal Denoisers in Multi-Dimensions
Tengyuan Liang
2025arXiv.org5 citations
Semantic Scholar
Distributional Shrinkage II: Optimal Transport Denoisers with Higher-Order Scores
Tengyuan Liang
2025arXiv.org4 citations
Semantic Scholar
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
Tengyuan Liang
2022Journal of machine learning research4 citations Open access
Semantic Scholar
A Convexified Matching Approach to Imputation and Individualized Inference
YoonHaeng Hur, Tengyuan Liang
20242 citations
Semantic Scholar
Universal prediction band via semi‐definite programming
Tengyuan Liang
2021Social Science Research Network2 citations Open access
Semantic Scholar
Experimental Design When N Equals One
Wenxuan Guo, Tengyuan Liang
20261 citations
Semantic Scholar
Gaussianized Design Optimization for Covariate Balance in Randomized Experiments
Wenxuan Guo, Tengyuan Liang, Panos Toulis
2025ACM Conference on Economics and Computation1 citations Open access
Semantic Scholar
Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation
Shuo-chieh Huang, Tengyuan Liang, R. Tsay
20241 citations
Semantic Scholar
Detecting Weak Distribution Shifts via Displacement Interpolation
YoonHaeng Hur, Tengyuan Liang
2023Journal of Business & Economic Statistics1 citations Open access
Semantic Scholar
Deep Learning for Individual Heterogeneity
Max H. Farrell, Tengyuan Liang, Sanjog Misra
2020arXiv.org1 citations
Semantic Scholar

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