A note on minimal d-separation trees for structural learning. - Binghui Liu; Jianhua Guo 005; Bing-Yi Jing (Artif. Intell., 2010)

WaVPeak: picking NMR peaks through wavelet-based smoothing and volume-based filtering. - Zhi Liu; Ahmed Abbas; Bing-Yi Jing; Xin Gao 001 (Bioinform., 2012)

A Bayesian feature selection paradigm for text classification. - Guozhong Feng; Jianhua Guo 005; Bing-Yi Jing; Lizhu Hao (Inf. Process. Manag., 2012)

Regularized maximum correntropy machine. - Jim Jing-Yan Wang; Yunji Wang; Bing-Yi Jing; Xin Gao 001 (Neurocomputing, 2015)

Feature subset selection using naive Bayes for text classification. - Guozhong Feng; Jianhua Guo 005; Bing-Yi Jing; Tieli Sun (Pattern Recognit. Lett., 2015)

Measuring the Clustering Strength of a Network via the Normalized Clustering Coefficient. - Ting Li; Xianshi Yu; Bing-Yi Jing (CoRR, 2019)

Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition. - Bing-Yi Jing; Ting Li; Zhongyuan Lyu; Dong Xia (CoRR, 2020)

Subsampling Spectral Clustering for Large-Scale Social Networks. - Jiayi Deng; Yi Ding; Yingqiu Zhu; Danyang Huang; Bingyi Jing; Bo Zhang (CoRR, 2021)

Soft BPR Loss for Dynamic Hard Negative Sampling in Recommender Systems. - Kexin Shi; Yun Zhang; Bingyi Jing; Wenjia Wang (CoRR, 2022)

Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression. - Wenjia Wang; Bing-Yi Jing (J. Mach. Learn. Res., 2022)

Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning. - Jing Zhang; Chi Zhang; Wenjia Wang; Bingyi Jing (NeurIPS, 2023)

APAC: Authorized Probability-controlled Actor-Critic For Offline Reinforcement Learning. - Jing Zhang; Chi Zhang; Wenjia Wang; Bing-Yi Jing (CoRR, 2023)

Data Upcycling Knowledge Distillation for Image Super-Resolution. - Yun Zhang; Wei Li 002; Simiao Li; Jie Hu 021; Hanting Chen; Hailing Wang; Zhijun Tu; Wenjia Wang; Bingyi Jing; Yunhe Wang 001 (CoRR, 2023)

Grouped spatial autoregressive model. - Danyang Huang; Wei Hu; Bingyi Jing; Bo Zhang (Comput. Stat. Data Anal., 2023)

DAGL-Faster: Domain adaptive faster r-cnn for vehicle object detection in rainy and foggy weather conditions. - Mingdi Hu; Yi Wu; Yize Yang; Jiulun Fan 001; Bingyi Jing (Displays, 2023)

High-Dimensional Volatility Matrix Estimation with Cross-Sectional Dependent and Heavy-Tailed Microstructural Noise. - Wanwan Liang; Ben Wu; Xinyan Fan; Bingyi Jing; Bo Zhang (J. Syst. Sci. Complex., 2023)

D2R2: Diffusion-based Representation with Random Distance Matching for Tabular Few-shot Learning. - Ruoxue Liu; Linjiajie Fang; Wenjia Wang; Bingyi Jing (NeurIPS, 2024)

Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model. - Jing Zhang; Linjiajie Fang; Kexin Shi; Wenjia Wang; Bingyi Jing (NeurIPS, 2024)

Exploring Learning Complexity for Downstream Data Pruning. - Wenyu Jiang; Zhenlong Liu; Zejian Xie; Songxin Zhang; Bingyi Jing; Hongxin Wei (CoRR, 2024)

Enhanced Bayesian Personalized Ranking for Robust Hard Negative Sampling in Recommender Systems. - Kexin Shi; Jing Zhang; Linjiajie Fang; Wenjia Wang; Bingyi Jing (CoRR, 2024)

ChineseSafe: A Chinese Benchmark for Evaluating Safety in Large Language Models. - Hengxiang Zhang; Hongfu Gao; Qiang Hu; Guanhua Chen; Lili Yang; Bingyi Jing; Hongxin Wei; Bing Wang; Haifeng Bai; Lei Yang (CoRR, 2024)

Two-way Node Popularity Model for Directed and Bipartite Networks. - Bing-Yi Jing; Ting Li; Jiangzhou Wang; Ya Wang (CoRR, 2024)

Prior-DualGAN: Rain rendering from coarse to fine. - Mingdi Hu; Jingbing Yang; Jianxun Yu; Bingyi Jing (Signal Process. Image Commun., 2024)

Subsampling spectral clustering for stochastic block models in large-scale networks. - Jiayi Deng; Danyang Huang; Yi Ding; Yingqiu Zhu; Bingyi Jing; Bo Zhang (Comput. Stat. Data Anal., 2024)

PractiCPP: a deep learning approach tailored for extremely imbalanced datasets in cell-penetrating peptide prediction. - Kexin Shi; Yuanpeng Xiong; Yu Wang 225; Yifan Deng; Wenjia Wang; Bingyi Jing; Xin Gao 001 (Bioinform., 2024)

Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning. - Linjiajie Fang; Ruoxue Liu; Jing Zhang; Wenjia Wang; Bingyi Jing (ICLR, 2025)

Exploring Learning Complexity for Efficient Downstream Dataset Pruning. - Wenyu Jiang; Zhenlong Liu; Zejian Xie; Songxin Zhang; Bingyi Jing; Hongxin Wei (ICLR, 2025)

Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution. - Simiao Li; Yun Zhang; Wei Li 002; Hanting Chen; Wenjia Wang; Bingyi Jing; Shaohui Lin; Jie Hu 021 (ICLR, 2025)

AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution. - Yun Zhang; Wei Li 002; Simiao Li; Hanting Chen; Zhijun Tu; Bingyi Jing; Shaohui Lin; Jie Hu 021; Wenjia Wang (ICLR, 2025)

Fine-tuning can Help Detect Pretraining Data from Large Language Models. - Hengxiang Zhang; Songxin Zhang; Bingyi Jing; Hongxin Wei (ICLR, 2025)

RITD: Real-time industrial text detection with boundary- and pixel-aware modules. - Yize Yang; Mingdi Hu; Jianxun Yu; Bingyi Jing (Displays, 2025)

Understanding asymptotic consistency and its unique advantages in large sample statistical inference. - Jiangzhou Wang; Binghui Liu; Bing-Yi Jing; Jianhua Guo 005 (J. Multivar. Anal., 2025)

Parametric Scaling Law of Tuning Bias in Conformal Prediction. - Hao Zeng 005; Kangdao Liu; Bingyi Jing; Hongxin Wei (CoRR, 2025)

Exploring Imbalanced Annotations for Effective In-Context Learning. - Hongfu Gao; Feipeng Zhang; Hao Zeng 005; Deyu Meng; Bingyi Jing; Hongxin Wei (CoRR, 2025)

Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Score. - Xuanning Zhou; Hao Zeng 005; Xiaobo Xia; Bingyi Jing; Hongxin Wei (CoRR, 2025)