Queue-aware energy-efficient scheduling in small-cell networks. - Hongxin Wei; Yang Yan; Limin Xiao; Shidong Zhou (ICC Workshops, 2014)

Feedback Reduction for Queue-aware Coordinated Multi-user Scheduling in Small-cell Networks. - Hongxin Wei; Xiaofeng Zhong; Ming Zhao 001; Yang Yan; Shidong Zhou (MILCOM, 2014)

Queue-aware energy-efficient scheduling and power allocation in small-cell networks with interference. - Hongxin Wei; Limin Xiao; Yunzhou Li; Shidong Zhou (WCNC, 2016)

Queue-aware energy-efficient scheduling and power allocation with feedback reduction in small-cell networks. - Hongxin Wei; Yunzhou Li; Limin Xiao; Shidong Zhou (Sci. China Inf. Sci., 2018)

Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization. - Hongxin Wei; Lei Feng 006; Xiangyu Chen; Bo An 001 (CVPR, 2020)

5G Embraces Satellites for 6G Ubiquitous IoT: Basic Models for Integrated Satellite Terrestrial Networks. - Xinran Fang; Te Wei; Wei Feng 001; Hongxin Wei; Yunfei Chen 001; Ning Ge 001; Cheng-Xiang Wang 001 (CoRR, 2020)

MetaInfoNet: Learning Task-Guided Information for Sample Reweighting. - Hongxin Wei; Lei Feng 006; Rundong Wang; Bo An 001 (CoRR, 2020)

Rethinking Blockchains in the Internet of Things Era from a Wireless Communication Perspective. - Hongxin Wei; Wei Feng 001; Yunfei Chen 001; Cheng-Xiang Wang 001; Ning Ge 001 (IEEE Netw., 2020)

Creating Efficient Blockchains for the Internet of Things by Coordinated Satellite-Terrestrial Networks. - Hongxin Wei; Wei Feng 001; Chi Zhang 001; Yunfei Chen 001; Yuguang Fang; Ning Ge 001 (IEEE Wirel. Commun., 2020)

Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management. - Rundong Wang; Hongxin Wei; Bo An 001; Zhouyan Feng; Jun Yao (AAAI, 2021)

Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix. - Ziqi Zhang; Yuexiang Li; Hongxin Wei; Kai Ma 002; Tao Xu; Yefeng Zheng 001 (BMVC, 2021)

Multiple-Instance Learning from Similar and Dissimilar Bags. - Lei Feng 006; Senlin Shu; Yuzhou Cao; Lue Tao; Hongxin Wei; Tao Xiang 001; Bo An 001; Gang Niu 001 (KDD, 2021)

Open-set Label Noise Can Improve Robustness Against Inherent Label Noise. - Hongxin Wei; Lue Tao; Renchunzi Xie; Bo An 001 (NeurIPS, 2021)

Embedding-Augmented Generalized Matrix Factorization for Recommendation With Implicit Feedback. - Lei Feng 006; Hongxin Wei; Qingyu Guo; Zhuoyi Lin; Bo An 001 (IEEE Intell. Syst., 2021)

GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation. - Renchunzi Xie; Hongxin Wei; Lei Feng 006; Bo An 001 (AAAI, 2022)

α-MF Detection Based on Spatial Correlation of Sea Clutter. - Hongxin Wei; Lin Zheng 001; Chao Yang 014; Ningyan Wei; Zhenghong Liu (ICCT, 2022)

Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets. - Hongxin Wei; Lue Tao; Renchunzi Xie; Lei Feng 006; Bo An 001 (ICML, 2022)

Mitigating Neural Network Overconfidence with Logit Normalization. - Hongxin Wei; Renchunzi Xie; Hao Cheng 014; Lei Feng 006; Bo An 001; Yixuan Li 001 (ICML, 2022)

Can Adversarial Training Be Manipulated By Non-Robust Features? - Lue Tao; Lei Feng 006; Hongxin Wei; Jinfeng Yi; Sheng-Jun Huang; Songcan Chen (NeurIPS, 2022)

ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection. - Huiping Zhuang; Zhenyu Weng; Hongxin Wei; Renchunzi Xie; Kar-Ann Toh; Zhiping Lin 001 (NeurIPS, 2022)

Logit Clipping for Robust Learning against Label Noise. - Hongxin Wei; Huiping Zhuang; Renchunzi Xie; Lei Feng 006; Gang Niu 001; Bo An 001; Yixuan Li 001 (CoRR, 2022)

A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. - Senlin Shu; Shuo He 001; Haobo Wang 001; Hongxin Wei; Tao Xiang 001; Lei Feng 006 (AAAI, 2023)

Mitigating Memorization of Noisy Labels by Clipping the Model Prediction. - Hongxin Wei; Huiping Zhuang; Renchunzi Xie; Lei Feng 006; Gang Niu 001; Bo An 001; Yixuan Li 001 (ICML, 2023)

In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. - Yuzhou Cao; Hussein Mozannar; Lei Feng 006; Hongxin Wei; Bo An 001 (NeurIPS, 2023)

Regression with Cost-based Rejection. - Xin Cheng 007; Yuzhou Cao; Haobo Wang 001; Hongxin Wei; Bo An 001; Lei Feng 006 (NeurIPS, 2023)

On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. - Renchunzi Xie; Hongxin Wei; Lei Feng 006; Yuzhou Cao; Bo An 001 (NeurIPS, 2023)

Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition. - Shuoyuan Wang; Jindong Wang 005; Huajun Xi; Bob Zhang 001; Lei Zhang 130; Hongxin Wei (CoRR, 2023)

Natural robustness of machine learning in the open world - Hongxin Wei (2023)

Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity. - Lei Feng 006; Senlin Shu; Yuzhou Cao; Lue Tao; Hongxin Wei; Tao Xiang 001; Bo An 001; Gang Niu 001 (IEEE Trans. Knowl. Data Eng., 2023)

Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition. - Shuoyuan Wang; Jindong Wang 001; Huajun Xi; Bob Zhang 001; Lei Zhang 130; Hongxin Wei (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023)

Deep Learning From Multiple Noisy Annotators as A Union. - Hongxin Wei; Renchunzi Xie; Lei Feng 006; Bo Han 003; Bo An 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning. - Shiyu Tian; Hongxin Wei; Yiqun Wang 001; Lei Feng 006 (CVPR, 2024)

Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. - Hao Chen 102; Jindong Wang 001; Ankit Shah 001; Ran Tao 013; Hongxin Wei; Xing Xie 001; Masashi Sugiyama; Bhiksha Raj (ICLR, 2024)

DOS: Diverse Outlier Sampling for Out-of-Distribution Detection. - Wenyu Jiang; Hao Cheng 014; Mingcai Chen; Chongjun Wang; Hongxin Wei (ICLR, 2024)

Consistent Multi-Class Classification from Multiple Unlabeled Datasets. - Zixi Wei; Senlin Shu; Yuzhou Cao; Hongxin Wei; Bo An 001; Lei Feng 006 (ICLR, 2024)

Conformal Prediction for Deep Classifier via Label Ranking. - Jianguo Huang; Huajun Xi; Linjun Zhang; Huaxiu Yao; Yue Qiu; Hongxin Wei (ICML, 2024)

Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss. - Zhenlong Liu; Lei Feng 006; Huiping Zhuang; Xiaofeng Cao; Hongxin Wei (ICML, 2024)

Open-Vocabulary Calibration for Fine-tuned CLIP. - Shuoyuan Wang; Jindong Wang 001; Guoqing Wang; Bob Zhang 001; Kaiyang Zhou; Hongxin Wei (ICML, 2024)

Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints. - Xiaobo Xia; Jiale Liu; Shaokun Zhang; Qingyun Wu; Hongxin Wei; Tongliang Liu (ICML, 2024)

On the Noise Robustness of In-Context Learning for Text Generation. - Hongfu Gao; Feipeng Zhang; Wenyu Jiang; Jun Shu; Feng Zheng; Hongxin Wei (NeurIPS, 2024)

GACL: Exemplar-Free Generalized Analytic Continual Learning. - Huiping Zhuang; Yizhu Chen; Di Fang 004; Run He; Kai Tong; Hongxin Wei; Ziqian Zeng; Cen Chen 002 (NeurIPS, 2024)

scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics. - Chuanyang Zheng; Yixuan Wang; Yuqi Cheng; Xuesong Wang; Hongxin Wei; Irwin King; Yu Li 006 (Briefings Bioinform., 2024)

Does Confidence Calibration Help Conformal Prediction? - Huajun Xi; Jianguo Huang; Lei Feng 006; Hongxin Wei (CoRR, 2024)

Open-Vocabulary Calibration for Vision-Language Models. - Shuoyuan Wang; Jindong Wang 005; Guoqing Wang; Bob Zhang 001; Kaiyang Zhou; Hongxin Wei (CoRR, 2024)

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

TorchCP: A Library for Conformal Prediction based on PyTorch. - Hongxin Wei; Jianguo Huang (CoRR, 2024)

Learning with Noisy Foundation Models. - Hao Chen 102; Jindong Wang 001; Zihan Wang; Ran Tao 013; Hongxin Wei; Xing Xie 001; Masashi Sugiyama; Bhiksha Raj (CoRR, 2024)

G-ACIL: Analytic Learning for Exemplar-Free Generalized Class Incremental Learning. - Huiping Zhuang; Yizhu Chen; Di Fang 004; Run He; Kai Tong; Hongxin Wei; Ziqian Zeng; Cen Chen 002 (CoRR, 2024)

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. - Minghao Liu 009; Zonglin Di; Jiaheng Wei; Zhongruo Wang; Hengxiang Zhang; Ruixuan Xiao; Haoyu Wang 001; Jinlong Pang; Hao Chen 102; Ankit Shah 001; Hongxin Wei; Xinlei He 001; et al. (CoRR, 2024)

Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models. - Shuoyuan Wang; Yixuan Li 001; Hongxin Wei (CoRR, 2024)

Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning. - Qiang Hu; Hengxiang Zhang; Hongxin Wei (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)

Analytic Continual Test-Time Adaptation for Multi-Modality Corruption. - Yufei Zhang; Yicheng Xu; Hongxin Wei; Zhiping Lin 001; Huiping Zhuang (CoRR, 2024)

Multiple-instance Learning from Triplet Comparison Bags. - Senlin Shu; Deng-Bao Wang; Suqin Yuan; Hongxin Wei; Jiuchuan Jiang; Lei Feng 006; Min-Ling Zhang (ACM Trans. Knowl. Discov. Data, 2024)

Multiple-Instance Learning from Pairwise Comparison Bags. - Shengjie Zhou; Senlin Shu; Haobo Wang 001; Hongxin Wei; Tao Xiang 001; Beibei Li 001 (ACM Trans. Intell. Syst. Technol., 2024)

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

Local-Prompt: Extensible Local Prompts for Few-Shot Out-of-Distribution Detection. - Fanhu Zeng; Zhen Cheng 003; Fei Zhu 004; Hongxin Wei; Xu-Yao Zhang (ICLR, 2025)

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

Does confidence calibration improve conformal prediction? - Huajun Xi; Jianguo Huang; Kangdao Liu; Lei Feng 006; Hongxin Wei (Trans. Mach. Learn. Res., 2025)

Robust Online Conformal Prediction under Uniform Label Noise. - Huajun Xi; Kangdao Liu; Hao Zeng 005; Wenguang Sun; Hongxin Wei (CoRR, 2025)

How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence. - Hyeong Kyu Choi; Maxim Khanov; Hongxin Wei; Yixuan Li 001 (CoRR, 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)

Efficient Membership Inference Attacks by Bayesian Neural Network. - Zhenlong Liu; Wenyu Jiang; Feng Zhou; Hongxin Wei (CoRR, 2025)

Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator. - Beier Luo; Shuoyuan Wang; Yixuan Li 001; 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)

Impact of Noisy Supervision in Foundation Model Learning. - Hao Chen 102; Zihan Wang; Ran Tao 013; Hongxin Wei; Xing Xie 001; Masashi Sugiyama; Bhiksha Raj; Jindong Wang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)