34 results on '"Tong, Hongzhi"'
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2. Nonasymptotic analysis of robust regression with modified Huber's loss
3. Functional linear regression with Huber loss
4. Moving quantile regression
5. Calibration of [formula omitted]insensitive loss in support vector machines regression
6. Spectral algorithms for learning with dependent observations
7. Learning performance of regularized moving least square regression
8. CLASSIFICATION WITH POLYNOMIAL KERNELS AND l 1 —COEFFICIENT REGULARIZATION
9. A Gradient Iteration Method for Functional Linear Regression in Reproducing Kernel Hilbert Spaces
10. Convergence rates of support vector machines regression for functional data
11. Support vector machines regression with [formula omitted]-regularizer
12. Distributed least squares prediction for functional linear regression
13. Analysis of Support Vector Machines Regression
14. Distributed least squares prediction for functional linear regression* This work was partially supported by the National Natural Science Foundation of China (Grant No. 11871438).
15. Optimal Decision of Agricultural Machinery Product Quality under the Regulation of Government Subsidy Policy
16. Analysis of Regression Algorithms with Unbounded Sampling
17. Pointwise weighted approximation by Bernstein operators
18. Calibration of ϵ−insensitive loss in support vector machines regression
19. Analysis of regularized least squares for functional linear regression model
20. Stechkin–Marchaud-Type Inequalities for Baskakov Polynomials
21. Support vector machines regression with unbounded sampling
22. Support vector machines regression with unbounded sampling.
23. A Note on Support Vector Machines with Polynomial Kernels
24. Learning Rates for ${l}^{1}$ -Regularized Kernel Classifiers
25. CLASSIFICATION WITH POLYNOMIAL KERNELS AND $l^1-$COEFFICIENT REGULARIZATION
26. Learning with Convex Loss and Indefinite Kernels
27. A Simpler Approach to Coefficient Regularized Support Vector Machines Regression
28. Learning Rates for -Regularized Kernel Classifiers
29. Fast learning rates for regularized regression algorithms
30. Support vector machines regression with l1-regularizer
31. Least Square Regression with lp-Coefficient Regularization
32. Learning rates for regularized classifiers using multivariate polynomial kernels
33. Analysis of Support Vector Machines Regression
34. Support vector machines regression with l1-regularizer
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