Divide and Conquer in High-dimensional Statistical Models

Research output

Research output per year 2020 2020 2021 2022 2023

• 20 RGC 21 - Publication in refereed journal

Research output per year

Research output per year

Search results

• 2023

  On Optimal Learning With Random Features

  Liu, J. & Lian, H., Nov 2023, In: IEEE Transactions on Neural Networks and Learning Systems. 34, 11, p. 9536-9541

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Supervised Learning 100%
  • Reproducing Kernel 100%
  • Hilbert Space 100%
  • Distributed Learning 100%
  • Regularity Condition 100%
  4 Citations (Scopus)

• Sketched approximation of regularized canonical correlation analysis

  Liu, J., Xu, W., Lin, H. & Lian, H., 2023, In: Communications in Statistics - Theory and Methods. 52, 19, p. 6960-6971

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Canonical Correlation Analysis 100%
  • Real Data 33%
  • Perturbation Theory 33%
  • Monte Carlo Study 33%
  • Multivariate Analysis 33%

• SPARSE AND LOW-RANK MATRIX QUANTILE ESTIMATION WITH APPLICATION TO QUADRATIC REGRESSION

  Lu, W., Zhu, Z. & Lian, H., Apr 2023, In: Statistica Sinica. 33, 2, p. 945-959

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  Open Access

  File

  • Matrix (Mathematics) 100%
  • Quantile 100%
  • Quantile Regression 60%
  • Covariate 40%
  • Real Data 20%
  7 Citations (Scopus)

  144 Downloads (CityUHK Scholars)
• 2022

  Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions

  Lv, S. & Lian, H., 2022, In: Journal of Machine Learning Research. 23, 2.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  Open Access

  File

  • Higher Dimensions 100%
  • Linear Models 100%
  • Parametric Model 66%
  • Parametric 33%
  • Least Square 33%
  13 Citations (Scopus)

  32 Downloads (CityUHK Scholars)

• High-dimensional quantile varying-coefficient models with dimension reduction

  Zhao, W., Li, R. & Lian, H., Jan 2022, In: Metrika. 85, 1, p. 1–19

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Smooth Function 100%
  • Response Variable 100%
  • Curse of Dimensionality 100%
  • Multivariate Functions 100%
  • Quantile Regression 100%
  2 Citations (Scopus)

• PARTIALLY LINEAR ADDITIVE FUNCTIONAL REGRESSION

  Liu, X., Lu, W., Lian, H., Liu, Y. & Zhu, Z., Oct 2022, In: Statistica Sinica. 32, 4, p. 2199-2216

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  Open Access

  File

  • Additive Functional 100%
  • Convergence Rate 50%
  • Regression Model 50%
  • Linear Part 50%
  • Asymptotic Normality 50%
  2 Citations (Scopus)

  113 Downloads (CityUHK Scholars)

• Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification

  Zhang, Y., Zhao, Y.-Y. & Lian, H., 2022, In: Journal of Machine Learning Research. 23, p. 1-24

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  Open Access

  File

  • Linear Part 100%
  • Support Vector Machine 100%
  • Approximates 50%
  • Convergence Rate 50%
  • Hilbert Space 50%
  3 Citations (Scopus)

  50 Downloads (CityUHK Scholars)
• 2021

  Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection

  Zhang, F., Li, R. & Lian, H., 8 Feb 2021, In: Information Sciences. 547, p. 244-254

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Approximates 100%
  • Hilbert Space 100%
  • Quantile Regression 100%
  • Spline 25%
  • Convergence Rate 25%
  9 Citations (Scopus)

• A semiparametric model for matrix regression

  Zhao, W., Zhang, X. & Lian, H., Apr 2021, In: Random Matrices: Theory and Application. 10, 2, 2250001.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Matrix (Mathematics) 100%
  • Additive Model 33%
  • Tensor 33%
  • Nonlinear Function 33%
  • Expressive Power 33%

• Distributed learning for sketched kernel regression

  Lian, H., Liu, J. & Fan, Z., Nov 2021, In: Neural Networks. 143, p. 368-376

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Divide and Conquer 100%
  • Least Square 25%
  • Hilbert Space 25%
  • Square Regression 25%
  10 Citations (Scopus)

• Learning Rate for Convex Support Tensor Machines

  Lian, H., Aug 2021, In: IEEE Transactions on Neural Networks and Learning Systems. 32, 8, p. 3755-3760 9174817.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Tensor 100%
  • Asymptotics 25%
  • Linear Function 25%
  • Statistical Property 25%
  • Least Square 25%
  5 Citations (Scopus)

• Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces

  Yang, G., Liu, X. & Lian, H., Oct 2021, In: Journal of Complexity. 66, 101568.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Hilbert Space 100%
  • Quantile Regression 100%
  • Linear Regression Analysis 100%
  • Amphetaminil 100%
  • Upper Bound 50%
  5 Citations (Scopus)

• Optimal prediction of quantile functional linear regression in reproducing kernel Hilbert spaces

  Li, R., Lu, W., Zhu, Z. & Lian, H., Mar 2021, In: Journal of Statistical Planning and Inference. 211, p. 162-170

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Hilbert Space 100%
  • Linear Regression Analysis 100%
  • Quantile 100%
  • Covariance 33%
  • Convergence Rate 33%
  8 Citations (Scopus)

• Sketched quantile additive functional regression

  Zhang, Y. & Lian, H., 21 Oct 2021, In: Neurocomputing. 461, p. 17-26

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Ridge Regression 100%
  • Additive Functional 100%
  • Quantile 100%
  • Numerical Analysis 50%
  • Hilbert Space 50%
• 2020

  Asymptotics of the Non-parametric Function for B-splines-based Estimation in Partially Linear Models

  Lian, H., Apr 2020, In: International Statistical Review. 88, 1, p. 142-154

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Asymptotics 100%
  • Parametric 100%
  • Linear Models 100%
  • B-Spline 100%
  • Linear Part 66%
  3 Citations (Scopus)

• FUNCTIONAL SLICED INVERSE REGRESSION IN A REPRODUCING KERNEL HILBERT SPACE: A THEORETICAL CONNECTION TO FUNCTIONAL LINEAR REGRESSION

  Wang, G. & Lian, H., Jan 2020, In: Statistica Sinica. 30, 1, p. 17-33

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  Open Access

  File

  • Hilbert Space 100%
  • Linear Regression Analysis 100%
  • Covariance 14%
  • Real Data 14%
  • Convergence Rate 14%
  72 Downloads (CityUHK Scholars)

• High-dimensional Quantile Tensor Regression

  Lu, W., Zhu, Z. & Lian, H., Oct 2020, In: Journal of Machine Learning Research. 21, 250.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Tensor 100%
  • Quantile 100%
  • Quantile Regression 75%
  • Covariate 50%
  • Asymptotic Property 25%
  17 Citations (Scopus)

• Nonlinear functional canonical correlation analysis via distance covariance

  Zhu, H., Li, R., Zhang, R. & Lian, H., Nov 2020, In: Journal of Multivariate Analysis. 180, 15 p., 104662.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  Open Access

  • Covariance 100%
  • Canonical Correlation Analysis 100%
  • Numerical Analysis 20%
  • Covariate 20%
  • Functional Data 20%
  3 Citations (Scopus)

• Partially functional linear regression in reproducing kernel Hilbert spaces

  Cui, X., Lin, H. & Lian, H., Oct 2020, In: Computational Statistics and Data Analysis. 150, 106978.

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Hilbert Space 100%
  • Linear Regression Analysis 100%
  • Linear Regression Model 33%
  • Asymptotic Normality 33%
  • Functional Principal Component Analysis 33%
  13 Citations (Scopus)

• Randomized sketches for kernel CCA

  Lian, H., Zhang, F. & Lu, W., Jul 2020, In: Neural Networks. 127, p. 29-37

  Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

  • Canonical Correlation Analysis 100%
  • Correlation Analysis 100%
  • Ridge Regression 33%
  • Kernel Ridge Regression 33%
  • Matrix (Mathematics) 16%
  5 Citations (Scopus)