Selected Publications and Talk Slides
Manuscripts patiently awaiting publication :)

Stein Neural Sampler (with Hu et al) Github

Statistical Optimality of Interpolated Nearest Neighbor Algorithms (with Xing, Y. and Song, Q.)

ModerateDimensional Inferences on Quadratic Functionals in Ordinary Least Squares (with Guo, X.)

Quadratic Discriminant Analysis under Moderate Dimension (with Yang, Q.)

Sparse and Lowrank Tensor Estimation via Cubic Sketchings (with Hao, B. and Zhang, A.)

Nonasymptotic Theory for Nonparametric Testing (with Yang, Y. and Shang, Z.)

Nonparametric Testing under Random Projection (with Liu, M. and Shang, Z.)

Optimal Tuning for DivideandConquer Kernel Ridge Regression with Massive Data (with Xu, G. and Shang, Z.)

Nonparametric Heterogeneity Testing For Massive Data (with Lu, J. and Liu, H.)

Nonparametric Bayesian Aggregation for Massive Data (with Shang, Z.)

Bootstrapping High Dimensional Time
Series (with Zhang, X.) See Talk
Slides

A Simple Averaged Confidence Interval
after Model Selection (with Xu, G. and Huang, J.)

Semiparametric Bernsteinvon Mises Theorem: Second Order Studies (with Yang, Y. and Dunson, D.)
Selected Publications
Refereed Publications

Liu, M. and Cheng, G. (2018) Early Stopping for Nonparametric Testing, NIPS

Xu, G., Shang, Z. and Cheng, G. (2018) Optimal Tuning for DivideandConquer Kernel Ridge Regression with Massive Data, ICML (oral), 80:54795487

Volgushev, S., Chao, S. and Cheng, G. (2018) Distributed Inference for Quantile Regression Processes, Annals of Statistics, To Appear.

Yu, Z., Levine, M. and Cheng, G. (2018) Minimax Optimal Estimation in Partially Linear
Additive Models under High Dimension, Bernoulli, To Appear.

Li, Q., Cheng, G., Fan, J. and Wang, Y. (2018) Embracing Blessing of Dimensionality in Factor Models, Journal of the American Statistical Association  Theory & Methods, 113, 380389

Hao, B. Sun, W., Liu, Y. and Cheng, G. (2018) Simultaneous Clustering and Estimation of Heterogeneous Graphical Models, Journal of Machine Learning Research, 18(217):1−58.

Shang, Z. and Cheng, G. (2017) Gaussian Approximation of General Nonparametric Posterior Distributions, Information and Inference, To Appear. In memory of Prof. Jayanta Ghosh

Shang, Z. and Cheng, G. (2017) Computational Limits of a Distributed Algorithm for Smoothing Spline, Journal of Machine Learning Research, 18(108):1−37.

Zhang, X. and Cheng, G. (2017) Guassian Approximation for High Dimensional Vector under Physical Dependence, Bernoulli, To Appear

Chao, S., Vogushev, S. and Cheng, G. (2017) Quantile Processes for Semi and Nonparametric Regression, Electronic Journal of Statistics, 11, 3272  3331

Zhang, X. and Cheng, G. (2017) Simultaneous Inference for HighDimensional Linear Models, Journal of the American Statistical Association  Theory & Methods, 112, 757768

Sun, W., Lu, J., Liu, H. and Cheng, G. (2017) Provable Sparse Tensor Decomposition, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 79, 899–916

Sun, W., Qiao, X. and Cheng, G. (2016) Stabilized Nearest Neighbor Classifier and Its Statistical Properties, Journal of the American Statistical Association  Theory & Methods, 111, 12541265

Minsker, S., Zhao, Y. and Cheng, G. (2016) Active Clinical Trials for
Personalized Medicine, Journal of the American Statistical Association  Theory & Methods, 111, 875887

Zhao, T., Cheng, G. and Liu, H. (2016) A Partially Linear Framework for Massive Heterogeneous Data. Annals of Statistics, 44, 14001437. See Talk Slides, Full Manuscript

Pati, D., Bhattacharya A., and Cheng, G. (2015) Optimal Bayesian estimation in random covariate design
with a rescaled Gaussian process prior, Journal of Machine Learning Research, 16, 2837−2851

Sun, W., Wang, Z., Liu, H. and Cheng, G. (2015) NonConvex Statistical Optimization for Sparse Tensor Graphical Model, NIPS (Acceptance Rate: 21.9%).

Shang, Z. and Cheng, G. (2015) Nonparametric
Inference in Generalized Functional Linear Models Annals of Statistics, 43, 17421773 (See Talk Slides)

Cheng, G. and Shang, Z. (2015) Joint Asymptotics for SemiNonparametric
Regression Models under Partially Linear Structure, Annals of Statistics, 43, 13511390 (See Talk Slides)

Cheng, G., Zhang, H.H. and Shang, Z. (2015) Sparse
and Efficient Estimation for Partial Spline Models with Increasing Dimension,
Annals of Institute of Statistical Mathematics, 67, 93127

Cheng, G. (2015) Moment Consistency of the Exchangeably
Weighted Bootstrap for Semiparametric MEstimation,
Scandinavian Journal of Statistics, 42, 665684

Cheng, G., Zhou, L. and Huang,
J.Z. (2014) Efficient Semiparametric Estimation in Generalized
Partially Linear Additive Models
for Longitudinal/Clustered Data, Bernoulli,
20, 141163

Shang, Z. and Cheng, G. (2013) Local and Global
Asymptotic Inference in Smoothing Spline Models, Annals of Statistics, 41, 26082638.
In the suppl file, [27] is Kosorok, M. R. (2008), and [38] is Pinelis, I. (1994, AoP).

Cheng, G. (2013). How Many Iterations are Sufficient for Efficient
Semiparametric Estimation?, Scandinavian
Journal of Statistics, 40, 592618 (See Talk Slides)

Zhang, H., Cheng, G. and Liu,
Y., (2011) Linear or Nonlinear? Automatic Discovery for
Partially Linear Models, Journal of the American Statistical Association  Theory
& Methods, 106, 10991112

Cheng,G. and Wang, X. (2011),
Semiparametric Additive Transformation Models under
Current Status Data, Electronic
Journal of Statistics, 5, 17351764

Cheng, G. and Huang,
J.Z., (2010) Bootstrap
Consistency for General Semiparametric Mestimation Annals
of Statistics, 38, 28842915 (See Talk Slides)

Cheng, G. (2009), Semiparametric
Additive Isotonic Regression Journal of Statistical Planning and
Inference, 139, 19801991

Cheng, G. and Kosorok, M.R. (2008), General
Frequentist Properties of the Posterior Profile Distribution Annals of
Statistics, 36, 18191853

Cheng, G.and Kosorok, M.R. (2008), Higher Order Semiparametric Frequentist Inference with the
Profile Sampler Annals of Statistics, 36, 17861818
NonRefereed Discussions

Chao, S.K. and Cheng, G. (2016) Discussion on "Of quantiles and expectiles: con
sistent scoring functions, Choquet representations and forecast rankings" by Werner
Ehm, Tilmann Gneiting, Alexander Jordan and Fabian Krger. Journal of the Royal Statistical Society: Series B (Statistical Methodology), To Appear

Leng,
C. and Cheng, G. (2012) Discussion
on “Probabilistic Index Models” by Thas, Neve, Clement and Ottoy, Journal of the Royal Statistical Society: Series B (Statistical Methodology)
, 74, 661662
Interdisciplinery Work

Liang, C., Cheng, G., Wilxon, D. and Balser, T. (2011) An Absorbing Markov Chain Approach to Understanding the Microbial Role in Soil Carbon Stabilization. Biogeochemistry
, 106, 303309
Talk Slides

T1. Bootstrapping High Dimensional Vector: Interplay between Dependence and
Dimensionality. Link (presented by my
coauthor Zhang at SAMSI
workshop)

T2. Nonparametric Inference in Functional Data. Link
(presented by my coauthor Shang at SAMSI
workshop)

T3. Nearest Neighbor Classifier with Optimal Stability. Link
(presented by my PhD student Sun
at ISBIS 2014 and SLDM Meeting)

T4. A Long March towards Joint Asymptotics: My 1^{st} Steps…. Link

T5. Semiparametric Model Based
Bootstrap. Link

T6. Bootstrap Consistency for General Semiparametric MEstimate. Link

T7.How Many Iterations are Sufficient
for Semiparametric Estimation? Link

T8. Inverse Problems in Semiparametric
Statistical Models. Link
