Lican Kang

24 papers A* 1Journal 21Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deep Bootstrap.
CoRR
Jinyuan Chang, Yuling Jiao, Lican Kang, Junjie Shi
2025 J jnl
Approximate Policy Iteration With Deep Minimax Average Bellman Error Minimization.
IEEE Trans. Neural Networks Learn. Syst.
Lican Kang, Yuhui Liu, Yuan Luo, Jerry Zhijian Yang, Han Yuan, Chang Zhu
2025 J jnl
Deep contrastive representation learning for supervised tasks.
Pattern Recognit.
Chenguang Duan, Yuling Jiao, Lican Kang, Jerry Zhijian Yang, Fusheng Zhou
2025 J jnl
Model Free Prediction With Uncertainty Assessment.
IEEE Trans. Inf. Theory
Yuling Jiao, Lican Kang, Jin Liu, Heng Peng, Heng Zuo
2025 J jnl
Opening the black box of deep learning: Validating the statistical association between explainable artificial intelligence (XAI) and clinical domain knowledge in fundus image-based glaucoma diagnosis.
CoRR
Han Yuan, Lican Kang, Yong Li
2025 J jnl
PDAS: a Newton-type method for L
Comput. Stat.
Ning Su, Yanyan Liu, Lican Kang
2025 J jnl
Schrödinger-Föllmer Sampler.
IEEE Trans. Inf. Theory
Jian Huang, Yuling Jiao, Lican Kang, Xu Liao, Jin Liu, Yanyan Liu
2024 J jnl
A communication-efficient method for generalized linear regression with ℓ
Commun. Stat. Simul. Comput.
Kunpeng Wang, Xuerui Li, Yanyan Liu, Lican Kang
2024 J jnl
Deep Nonparametric Quantile Regression under Covariate Shift.
J. Mach. Learn. Res.
Xingdong Feng, Xin He, Yuling Jiao, Lican Kang, Caixing Wang
2024 J jnl
Latent Schr{\"o}dinger Bridge Diffusion Model for Generative Learning.
CoRR
Yuling Jiao, Lican Kang, Huazhen Lin, Jin Liu, Heng Zuo
2024 J jnl
Model Free Prediction with Uncertainty Assessment.
CoRR
Yuling Jiao, Lican Kang, Jin Liu, Heng Peng, Heng Zuo
2024 J jnl
Newton-Raphson Meets Sparsity: Sparse Learning Via a Novel Penalty and a Fast Solver.
IEEE Trans. Neural Networks Learn. Syst.
Yongxiu Cao, Lican Kang, Xuerui Li, Yanyan Liu, Yuan Luo, Yueyong Shi
2023 — conf
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
Han Yuan, Mingxuan Liu, Lican Kang, Chenkui Miao, Ying Wu
2023 J jnl
Deep estimation for
Inf. Sci.
Lican Kang, Xu Liao, Jin Liu, Yuan Luo
2023 — conf
Error Analysis of Fitted Q-iteration with ReLU-activated Deep Neural Networks.
Tiny Papers @ ICLR
Lican Kang, Han Yuan, Chang Zhu
2023 A* conf
Fast Excess Risk Rates via Offset Rademacher Complexity.
ICML
Chenguang Duan, Yuling Jiao, Lican Kang, Xiliang Lu, Jerry Zhijian Yang
2023 J jnl
Global Optimization via Schrödinger-Föllmer Diffusion.
SIAM J. Control. Optim.
Yin Dai, Yuling Jiao, Lican Kang, Xiliang Lu, Jerry Zhijian Yang
2023 J jnl
Over-parameterized Deep Nonparametric Regression for Dependent Data with Its Applications to Reinforcement Learning.
J. Mach. Learn. Res.
Xingdong Feng, Yuling Jiao, Lican Kang, Baqun Zhang, Fan Zhou
2022 J jnl
A data-driven line search rule for support recovery in high-dimensional data analysis.
Comput. Stat. Data Anal.
Peili Li, Yuling Jiao, Xiliang Lu, Lican Kang
2022 J jnl
An empirical study of the effect of background data size on the stability of SHapley Additive exPlanations (SHAP) for deep learning models.
CoRR
Han Yuan, Mingxuan Liu, Lican Kang, Chenkui Miao, Ying Wu
2022 J jnl
GSDAR: a fast Newton algorithm for ℓ
Comput. Stat.
Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu
2021 J jnl
A Data-Driven Line Search Rule for Support Recovery in High-dimensional Data Analysis.
CoRR
Peili Li, Yuling Jiao, Xiliang Lu, Lican Kang
2021 J jnl
Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity.
CoRR
Yuling Jiao, Lican Kang, Yanyan Liu, Youzhou Zhou
2020 J jnl
A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models.
CoRR
Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu