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2020 – today
- 2024
[j7]Kunpeng Wang, Xuerui Li, Yanyan Liu
, Lican Kang:
A communication-efficient method for generalized linear regression with ℓ 0 regularization. Commun. Stat. Simul. Comput. 53(8): 3850-3867 (2024)- [j6]Yongxiu Cao, Lican Kang, Xuerui Li, Yanyan Liu, Yuan Luo, Yueyong Shi:
Newton-Raphson Meets Sparsity: Sparse Learning Via a Novel Penalty and a Fast Solver. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12057-12067 (2024) - [i6]Yuling Jiao, Lican Kang, Huazhen Lin, Jin Liu, Heng Zuo:
Latent Schr{\"o}dinger Bridge Diffusion Model for Generative Learning. CoRR abs/2404.13309 (2024) - [i5]Yuling Jiao, Lican Kang, Jin Liu, Heng Peng, Heng Zuo:
Model Free Prediction with Uncertainty Assessment. CoRR abs/2405.12684 (2024) - 2023
- [j5]Lican Kang, Xu Liao, Jin Liu, Yuan Luo:
Deep estimation for Q⁎ with minimax Bellman error minimization. Inf. Sci. 648: 119565 (2023) - [j4]Xingdong Feng, Yuling Jiao, Lican Kang, Baqun Zhang, Fan Zhou:
Over-parameterized Deep Nonparametric Regression for Dependent Data with Its Applications to Reinforcement Learning. J. Mach. Learn. Res. 24: 383:1-383:40 (2023) - [j3]Yin Dai, Yuling Jiao, Lican Kang, Xiliang Lu, Jerry Zhijian Yang:
Global Optimization via Schrödinger-Föllmer Diffusion. SIAM J. Control. Optim. 61(5): 2953-2980 (2023) - [c3]Lican Kang, Han Yuan, Chang Zhu:
Error Analysis of Fitted Q-iteration with ReLU-activated Deep Neural Networks. Tiny Papers @ ICLR 2023 - [c2]Han Yuan, Mingxuan Liu, Lican Kang, Chenkui Miao, Ying Wu:
An Empirical Study of the Effect of Background Data Size on the Stability of SHapley Additive exPlanations (SHAP) for Deep Learning Models. Tiny Papers @ ICLR 2023 - [c1]Chenguang Duan, Yuling Jiao, Lican Kang, Xiliang Lu, Jerry Zhijian Yang:
Fast Excess Risk Rates via Offset Rademacher Complexity. ICML 2023: 8697-8716 - 2022
- [j2]Peili Li, Yuling Jiao, Xiliang Lu, Lican Kang:
A data-driven line search rule for support recovery in high-dimensional data analysis. Comput. Stat. Data Anal. 174: 107524 (2022) - [j1]Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu:
GSDAR: a fast Newton algorithm for ℓ 0 regularized generalized linear models with statistical guarantee. Comput. Stat. 37(1): 507-533 (2022) - [i4]Han Yuan, Mingxuan Liu, Lican Kang, Chenkui Miao, Ying Wu:
An empirical study of the effect of background data size on the stability of SHapley Additive exPlanations (SHAP) for deep learning models. CoRR abs/2204.11351 (2022) - 2021
- [i3]Yuling Jiao, Lican Kang, Yanyan Liu, Youzhou Zhou:
Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity. CoRR abs/2107.04766 (2021) - [i2]Peili Li, Yuling Jiao, Xiliang Lu, Lican Kang:
A Data-Driven Line Search Rule for Support Recovery in High-dimensional Data Analysis. CoRR abs/2111.10806 (2021) - 2020
- [i1]Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu:
A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models. CoRR abs/2001.05819 (2020)
Coauthor Index
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