E-LIB Suche - Ergebnisse für: Kang, Lican

1

PDAS: a Newton-type method for $$L_0$$ regularized accelera..:

Su, Ning ; Liu, Yanyan ; Kang, Lican
Computational Statistics. , 2024

Link: https://doi.org/10.1007/..

2

Newton–Raphson Meets Sparsity: Sparse Learning Via a Novel ..:

Cao, Yongxiu ; Kang, Lican ; Li, Xuerui...
IEEE Transactions on Neural Networks and Learning Systems. , 2024

Link: https://doi.org/10.1109/..

3

Approximate Policy Iteration With Deep Minimax Average Bell..:

Kang, Lican ; Liu, Yuhui ; Luo, Yuan...
IEEE Transactions on Neural Networks and Learning Systems. , 2024

Link: https://doi.org/10.1109/..

4

Computation and analysis of change points with different ju..:

Huang, Jian ; Jiao, Yuling ; Kang, Lican..
Statistical Papers. 65 (2023) 3 - p. 1703-1729 , 2023

Link: https://doi.org/10.1007/..

5

Deep estimation for Q⁎ with minimax Bellman error minimizat..:

Kang, Lican ; Liao, Xu ; Liu, Jin.
Information Sciences. 648 (2023) - p. 119565 , 2023

Link: https://doi.org/10.1016/..

6

Global Optimization via Schrödinger–Föllmer Diffusion:

Dai, Yin ; Jiao, Yuling ; Kang, Lican..
SIAM Journal on Control and Optimization. 61 (2023) 5 - p. 2953-2980 , 2023

Link: https://doi.org/10.1137/..

7

A data-driven line search rule for support recovery in high..:

Li, Peili ; Jiao, Yuling ; Lu, Xiliang.
Computational Statistics & Data Analysis. 174 (2022) - p. 107524 , 2022

Link: https://doi.org/10.1016/..

8

A communication-efficient method for generalized linear reg..:

Wang, Kunpeng ; Li, Xuerui ; Liu, Yanyan.
Communications in Statistics - Simulation and Computation. , 2022

Link: https://doi.org/10.1080/..

9

A communication-efficient method for ℓ0 regularization line..:

Kang, Lican ; Li, Xuerui ; Liu, Yanyan..
Journal of Statistical Computation and Simulation. 93 (2022) 4 - p. 533-555 , 2022

Link: https://doi.org/10.1080/..

10

GSDAR: a fast Newton algorithm for $$\ell _0$$ regularized ..:

Huang, Jian ; Jiao, Yuling ; Kang, Lican...
Computational Statistics. 37 (2021) 1 - p. 507-533 , 2021

Link: https://doi.org/10.1007/..

11

Fitting sparse linear models under the sufficient and neces..:

Huang, Jian ; Jiao, Yuling ; Kang, Lican.
Statistics & Probability Letters. 168 (2021) - p. 108925 , 2021

Link: https://doi.org/10.1016/..

12

Lipschitz Transport Maps via the Follmer Flow:

Dai, Yin ; Gao, Yuan ; Huang, Jian...
http://arxiv.org/abs/2309.03490. , 2023

Link: http://arxiv.org/abs/230..

13

An empirical study of the effect of background data size on..:

Yuan, Han ; Liu, Mingxuan ; Kang, Lican..
http://arxiv.org/abs/2204.11351. , 2022

Link: http://arxiv.org/abs/220..

14

Global Optimization via Schr{\"o}dinger-F{\"o}llmer Diffusi..:

Dai, Yin ; Jiao, Yuling ; Kang, Lican..
http://arxiv.org/abs/2111.00402. , 2021

Link: http://arxiv.org/abs/211..

15

Schr{\"o}dinger-F{\"o}llmer Sampler: Sampling without Ergod..:

Huang, Jian ; Jiao, Yuling ; Kang, Lican...
http://arxiv.org/abs/2106.10880. , 2021

Link: http://arxiv.org/abs/210..