Incremental Matrix Factorization: A Linear Feature Transformation Perspective. - Xunpeng Huang; Le Wu; Enhong Chen; Hengshu Zhu; Qi Liu 003; Yijun Wang 002 (IJCAI, 2017)

Generalized Neural Graph Embedding with Matrix Factorization. - Junliang Guo; Linli Xu; Xunpeng Huang; Enhong Chen (CoRR, 2017)

Confidence-Aware Matrix Factorization for Recommender Systems. - Chao Wang 086; Qi Liu 003; Runze Wu 001; Enhong Chen; Chuanren Liu; Xunpeng Huang; Zhenya Huang (AAAI, 2018)

Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective. - Junliang Guo; Linli Xu; Xunpeng Huang; Enhong Chen (DASFAA (1), 2018)

Finding potential lenders in P2P lending: A Hybrid Random Walk Approach. - Hefu Zhang; Hongke Zhao; Qi Liu 003; Tong Xu 001; Enhong Chen; Xunpeng Huang (Inf. Sci., 2018)

SPAN: A Stochastic Projected Approximate Newton Method. - Xunpeng Huang; Xianfeng Liang; Zhengyang Liu 002; Lei Li 005; Yue Yu; Yitan Li (AAAI, 2020)

SPAN: A Stochastic Projected Approximate Newton Method. - Xunpeng Huang; Xianfeng Liang; Zhengyang Liu 002; Yue Yu; Lei Li 005 (CoRR, 2020)

Adaptive Gradient Methods Can Be Provably Faster than SGD after Finite Epochs. - Xunpeng Huang; Hao Zhou 012; Runxin Xu; Zhe Wang; Lei Li 005 (CoRR, 2020)

ACMo: Angle-Calibrated Moment Methods for Stochastic Optimization. - Xunpeng Huang; Runxin Xu; Hao Zhou 012; Zhe Wang; Zhengyang Liu 002; Lei Li 005 (AAAI, 2021)

Mean-Field Analysis of Two-Layer Neural Networks: Global Optimality with Linear Convergence Rates. - Jingwei Zhang; Xunpeng Huang (CoRR, 2022)

Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach. - Xunpeng Huang; Hanze Dong; Yifan Hao 002; Yian Ma; Tong Zhang 001 (CoRR, 2023)

Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo. - Xunpeng Huang; Difan Zou; Hanze Dong; Yi-An Ma; Tong Zhang 001 (COLT, 2024)

Reverse Diffusion Monte Carlo. - Xunpeng Huang; Hanze Dong; Yifan Hao 002; Yian Ma; Tong Zhang 001 (ICLR, 2024)

Faster Sampling via Stochastic Gradient Proximal Sampler. - Xunpeng Huang; Difan Zou; Hanze Dong; Yian Ma; Tong Zhang 001 (ICML, 2024)

Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference. - Xunpeng Huang; Difan Zou; Hanze Dong; Yi Zhang; Yian Ma; Tong Zhang 001 (NeurIPS, 2024)

An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling. - Xunpeng Huang; Hanze Dong; Difan Zou; Tong Zhang 001 (CoRR, 2024)

What Makes In-context Learning Effective for Mathematical Reasoning: A Theoretical Analysis. - Jia-Yu Liu 001; Zhenya Huang; Chaokun Wang; Xunpeng Huang; Chengxiang Zhai; Enhong Chen (CoRR, 2024)

Capturing Conditional Dependence via Auto-regressive Diffusion Models. - Xunpeng Huang; Yujin Han; Difan Zou; Yian Ma; Tong Zhang 001 (CoRR, 2025)

Multi-Step Consistency Models: Fast Generation with Theoretical Guarantees. - Nishant Jain; Xunpeng Huang; Yian Ma; Tong Zhang 001 (CoRR, 2025)

Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion. - Xunpeng Huang; Yingyu Lin; Nikki Lijing Kuang; Hanze Dong; Difan Zou; Yian Ma; Tong Zhang 001 (CoRR, 2025)