Lican Kang

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 14

Top Topics

Error Minimization

Generalized Linear Models

Top Venues

Tiny Papers @ ICLR

Comput. Stat. Data Anal.

Publications

Yuling Jiao, Lican Kang, Huazhen Lin, Jin Liu, Heng Zuo
Latent Schr{\"o}dinger Bridge Diffusion Model for Generative Learning. CoRR (2024)
Yuling Jiao, Lican Kang, Jin Liu, Heng Peng, Heng Zuo
Model Free Prediction with Uncertainty Assessment. CoRR (2024)
Lican Kang, Xu Liao, Jin Liu, Yuan Luo
with minimax Bellman error minimization. Inf. Sci. 648 (2023)
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)
Chenguang Duan, Yuling Jiao, Lican Kang, Xiliang Lu, Jerry Zhijian Yang
Fast Excess Risk Rates via Offset Rademacher Complexity. ICML (2023)
Lican Kang, Han Yuan, Chang Zhu
Error Analysis of Fitted Q-iteration with ReLU-activated Deep Neural Networks. Tiny Papers @ ICLR (2023)
Yin Dai, Yuling Jiao, Lican Kang, Xiliang Lu, Jerry Zhijian Yang
Global Optimization via Schrödinger-Föllmer Diffusion. SIAM J. Control. Optim. 61 (5) (2023)
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 (2022)
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 (2022)
Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu
regularized generalized linear models with statistical guarantee. Comput. Stat. 37 (1) (2022)
Yuling Jiao, Lican Kang, Yanyan Liu, Youzhou Zhou
Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity. CoRR (2021)
Peili Li, Yuling Jiao, Xiliang Lu, Lican Kang
A Data-Driven Line Search Rule for Support Recovery in High-dimensional Data Analysis. CoRR (2021)
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 (2020)
Jian Huang, Yuling Jiao, Lican Kang, Jin Liu, Yanyan Liu, Xiliang Lu, Yuanyuan Yang
On Newton Screening. CoRR (2020)