Hongxin Wei - RankMe

112 papers A* 33A 2B 1Journal 72Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Conditional Performance Guarantee for Large Reasoning Models. CoRR Jianguo Huang, Hao Zeng, Bingyi Jing, Hongxin Wei, Bo An
2026	J	`jnl`	Distribution-informed Efficient Conformal Prediction for Full Ranking. CoRR Wenbo Liao, Huipeng Huang, Chen Jia, Huajun Xi, Hao Zeng, Hongxin Wei
2026	J	`jnl`	HyPAC: Cost-Efficient LLMs-Human Hybrid Annotation with PAC Error Guarantees. CoRR Hao Zeng, Huipeng Huang, Xinhao Qu, Jianguo Huang, Bingyi Jing, Hongxin Wei
2026	J	`jnl`	MarsRetrieval: Benchmarking Vision-Language Models for Planetary-Scale Geospatial Retrieval on Mars. CoRR Shuoyuan Wang, Yiran Wang, Hongxin Wei
2026	J	`jnl`	Natural Language-Driven Global Mapping of Martian Landforms. CoRR Yiran Wang, Shuoyuan Wang, Zhaoran Wei, Jiannan Zhao, Zhonghua Yao, Zejian Xie, Songxin Zhang, Jun Huang, Bingyi Jing, Hongxin Wei
2026	A*	`conf`	Online Conformal Selection with Accept-to-Reject Changes. AAAI Kangdao Liu, Huajun Xi, Chi Man Vong, Hongxin Wei
2026	J	`jnl`	Provable Model Provenance Set for Large Language Models. CoRR Xiaoqi Qiu, Hao Zeng, Zhiyu Hou, Hongxin Wei
2026	J	`jnl`	RACER: Risk-Aware Calibrated Efficient Routing for Large Language Models. CoRR Sai Hao, Hao Zeng, Hongxin Wei, Bingyi Jing
2026	J	`jnl`	ST-BCP: Tightening Coverage Bound for Backward Conformal Prediction via Non-Conformity Score Transformation. CoRR Junxian Liu, Hao Zeng, Hongxin Wei
2026	J	`jnl`	Toward Early Quality Assessment of Text-to-Image Diffusion Models. CoRR Huanlei Guo, Hongxin Wei, Bingyi Jing
2026	J	`jnl`	Unlocking the Pre-Trained Model as a Dual-Alignment Calibrator for Post-Trained LLMs. CoRR Beier Luo, Cheng Wang, Hongxin Wei, Sharon Li, Xuefeng Du
2025	A*	`conf`	Analytic Continual Test-Time Adaptation for Multi-Modality Corruption. ACM Multimedia Yufei Zhang, Yicheng Xu, Hongxin Wei, Zhiping Lin, Xiaofeng Zou, Cen Chen, Huiping Zhuang
2025	A	`conf`	C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction Sets. ECAI Kangdao Liu, Hao Zeng, Jianguo Huang, Huiping Zhuang, Chi-Man Vong, Hongxin Wei
2025	J	`jnl`	Detecting Distillation Data from Reasoning Models. CoRR Hengxiang Zhang, Hyeong Kyu Choi, Sharon Li, Hongxin Wei
2025	J	`jnl`	Does confidence calibration improve conformal prediction? Trans. Mach. Learn. Res. Huajun Xi, Jianguo Huang, Kangdao Liu, Lei Feng, Hongxin Wei
2025	J	`jnl`	Efficient Membership Inference Attacks by Bayesian Neural Network. CoRR Zhenlong Liu, Wenyu Jiang, Feng Zhou, Hongxin Wei
2025	J	`jnl`	Exploring Imbalanced Annotations for Effective In-Context Learning. CoRR Hongfu Gao, Feipeng Zhang, Hao Zeng, Deyu Meng, Bingyi Jing, Hongxin Wei
2025	A*	`conf`	Exploring Learning Complexity for Efficient Downstream Dataset Pruning. ICLR Wenyu Jiang, Zhenlong Liu, Zejian Xie, Songxin Zhang, Bingyi Jing, Hongxin Wei
2025	A*	`conf`	Fine-tuning can Help Detect Pretraining Data from Large Language Models. ICLR Hengxiang Zhang, Songxin Zhang, Bingyi Jing, Hongxin Wei
2025	J	`jnl`	High-Power Training Data Identification with Provable Statistical Guarantees. CoRR Zhenlong Liu, Hao Zeng, Weiran Huang, Hongxin Wei
2025	A*	`conf`	How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence. ICML Hyeong Kyu Choi, Maxim Khanov, Hongxin Wei, Yixuan Li
2025	J	`jnl`	How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence. CoRR Hyeong Kyu Choi, Maxim Khanov, Hongxin Wei, Yixuan Li
2025	J	`jnl`	Impact of Noisy Supervision in Foundation Model Learning. IEEE Trans. Pattern Anal. Mach. Intell. Hao Chen, Zihan Wang, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj, Jindong Wang
2025	A*	`conf`	Local-Prompt: Extensible Local Prompts for Few-Shot Out-of-Distribution Detection. ICLR Fanhu Zeng, Zhen Cheng, Fei Zhu, Hongxin Wei, Xu-Yao Zhang
2025	A*	`conf`	Mitigating Stereotypes in Text-to-Image Generation: A Novel Perspective of Selective Neural Suppression. ACM Multimedia Junlei Zhou, Jiashi Gao, Xinwei Guo, Haiyan Wu, Quanying Liu, Xiangyu Zhao, Hongxin Wei, Xin Yao, Xuetao Wei
2025	J	`jnl`	Multi-Condition Conformal Selection. CoRR Qingyang Hao, Wenbo Liao, Bingyi Jing, Hongxin Wei
2025	J	`jnl`	Online Conformal Selection with Accept-to-Reject Changes. CoRR Kangdao Liu, Huajun Xi, Chi-Man Vong, Hongxin Wei
2025	J	`jnl`	PAC Reasoning: Controlling the Performance Loss for Efficient Reasoning. CoRR Hao Zeng, Jianguo Huang, Bingyi Jing, Hongxin Wei, Bo An
2025	A*	`conf`	Parametric Scaling Law of Tuning Bias in Conformal Prediction. ICML Hao Zeng, Kangdao Liu, Bingyi Jing, Hongxin Wei
2025	J	`jnl`	Parametric Scaling Law of Tuning Bias in Conformal Prediction. CoRR Hao Zeng, Kangdao Liu, Bingyi Jing, Hongxin Wei
2025	J	`jnl`	Robust Online Conformal Prediction under Uniform Label Noise. CoRR Huajun Xi, Kangdao Liu, Hao Zeng, Wenguang Sun, Hongxin Wei
2025	J	`jnl`	Selective Labeling with False Discovery Rate Control. CoRR Huipeng Huang, Wenbo Liao, Huajun Xi, Hao Zeng, Mengchen Zhao, Hongxin Wei
2025	J	`jnl`	Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Score. CoRR Xuanning Zhou, Hao Zeng, Xiaobo Xia, Bingyi Jing, Hongxin Wei
2025	J	`jnl`	TorchCP: A Python Library for Conformal Prediction. J. Mach. Learn. Res. Jianguo Huang, Jianqing Song, Xuanning Zhou, Bingyi Jing, Hongxin Wei
2025	A*	`conf`	Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models. ICML Shuoyuan Wang, Yixuan Li, Hongxin Wei
2025	J	`jnl`	Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator. CoRR Beier Luo, Shuoyuan Wang, Yixuan Li, Hongxin Wei
2024	J	`jnl`	Analytic Continual Test-Time Adaptation for Multi-Modality Corruption. CoRR Yufei Zhang, Yicheng Xu, Hongxin Wei, Zhiping Lin, Huiping Zhuang
2024	J	`jnl`	Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. CoRR Minghao Liu, Zonglin Di, Jiaheng Wei, Zhongruo Wang, Hengxiang Zhang, Ruixuan Xiao, Haoyu Wang, Jinlong Pang, Hao Chen, Ankit Shah, Hongxin Wei, Xinlei He, Zhaowei Zhao, Haobo Wang, Lei Feng, Jindong Wang, James Davis, Yang Liu
2024	J	`jnl`	ChineseSafe: A Chinese Benchmark for Evaluating Safety in Large Language Models. CoRR Hengxiang Zhang, Hongfu Gao, Qiang Hu, Guanhua Chen, Lili Yang, Bingyi Jing, Hongxin Wei, Bing Wang, Haifeng Bai, Lei Yang
2024	A*	`conf`	Conformal Prediction for Deep Classifier via Label Ranking. ICML Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei
2024	A*	`conf`	Consistent Multi-Class Classification from Multiple Unlabeled Datasets. ICLR Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng
2024	A*	`conf`	CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning. CVPR Shiyu Tian, Hongxin Wei, Yiqun Wang, Lei Feng
2024	A*	`conf`	DOS: Diverse Outlier Sampling for Out-of-Distribution Detection. ICLR Wenyu Jiang, Hao Cheng, Mingcai Chen, Chongjun Wang, Hongxin Wei
2024	J	`jnl`	Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning. CoRR Qiang Hu, Hengxiang Zhang, Hongxin Wei
2024	J	`jnl`	Does Confidence Calibration Help Conformal Prediction? CoRR Huajun Xi, Jianguo Huang, Lei Feng, Hongxin Wei
2024	J	`jnl`	Exploring Learning Complexity for Downstream Data Pruning. CoRR Wenyu Jiang, Zhenlong Liu, Zejian Xie, Songxin Zhang, Bingyi Jing, Hongxin Wei
2024	J	`jnl`	Fine-tuning can Help Detect Pretraining Data from Large Language Models. CoRR Hengxiang Zhang, Songxin Zhang, Bingyi Jing, Hongxin Wei
2024	J	`jnl`	G-ACIL: Analytic Learning for Exemplar-Free Generalized Class Incremental Learning. CoRR Huiping Zhuang, Yizhu Chen, Di Fang, Run He, Kai Tong, Hongxin Wei, Ziqian Zeng, Cen Chen
2024	A*	`conf`	GACL: Exemplar-Free Generalized Analytic Continual Learning. NeurIPS Huiping Zhuang, Yizhu Chen, Di Fang, Run He, Kai Tong, Hongxin Wei, Ziqian Zeng, Cen Chen
2024	J	`jnl`	Learning with Noisy Foundation Models. CoRR Hao Chen, Jindong Wang, Zihan Wang, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
2024	A*	`conf`	Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss. ICML Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei
2024	J	`jnl`	Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss. CoRR Zhenlong Liu, Lei Feng, Huiping Zhuang, Xiaofeng Cao, Hongxin Wei
2024	J	`jnl`	Multiple-Instance Learning from Pairwise Comparison Bags. ACM Trans. Intell. Syst. Technol. Shengjie Zhou, Senlin Shu, Haobo Wang, Hongxin Wei, Tao Xiang, Beibei Li
2024	J	`jnl`	Multiple-instance Learning from Triplet Comparison Bags. ACM Trans. Knowl. Discov. Data Senlin Shu, Deng-Bao Wang, Suqin Yuan, Hongxin Wei, Jiuchuan Jiang, Lei Feng, Min-Ling Zhang
2024	A*	`conf`	On the Noise Robustness of In-Context Learning for Text Generation. NeurIPS Hongfu Gao, Feipeng Zhang, Wenyu Jiang, Jun Shu, Feng Zheng, Hongxin Wei
2024	J	`jnl`	On the Noise Robustness of In-Context Learning for Text Generation. CoRR Hongfu Gao, Feipeng Zhang, Wenyu Jiang, Jun Shu, Feng Zheng, Hongxin Wei
2024	A*	`conf`	Open-Vocabulary Calibration for Fine-tuned CLIP. ICML Shuoyuan Wang, Jindong Wang, Guoqing Wang, Bob Zhang, Kaiyang Zhou, Hongxin Wei
2024	J	`jnl`	Open-Vocabulary Calibration for Vision-Language Models. CoRR Shuoyuan Wang, Jindong Wang, Guoqing Wang, Bob Zhang, Kaiyang Zhou, Hongxin Wei
2024	A*	`conf`	Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints. ICML Xiaobo Xia, Jiale Liu, Shaokun Zhang, Qingyun Wu, Hongxin Wei, Tongliang Liu
2024	J	`jnl`	TorchCP: A Library for Conformal Prediction based on PyTorch. CoRR Hongxin Wei, Jianguo Huang
2024	J	`jnl`	Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models. CoRR Shuoyuan Wang, Yixuan Li, Hongxin Wei
2024	A*	`conf`	Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. ICLR Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
2024	J	`jnl`	scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics. Briefings Bioinform. Chuanyang Zheng, Yixuan Wang, Yuqi Cheng, Xuesong Wang, Hongxin Wei, Irwin King, Yu Li
2023	A*	`conf`	A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. AAAI Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng
2023	J	`jnl`	A Generalized Unbiased Risk Estimator for Learning with Augmented Classes. CoRR Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng
2023	J	`jnl`	Conformal Prediction for Deep Classifier via Label Ranking. CoRR Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei
2023	J	`jnl`	CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning. CoRR Shiyu Tian, Hongxin Wei, Yiqun Wang, Lei Feng
2023	J	`jnl`	DOS: Diverse Outlier Sampling for Out-of-Distribution Detection. CoRR Wenyu Jiang, Hao Cheng, Mingcai Chen, Chongjun Wang, Hongxin Wei
2023	J	`jnl`	Deep Learning From Multiple Noisy Annotators as A Union. IEEE Trans. Neural Networks Learn. Syst. Hongxin Wei, Renchunzi Xie, Lei Feng, Bo Han, Bo An
2023	A*	`conf`	In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. NeurIPS Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An
2023	J	`jnl`	In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer. CoRR Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An
2023	A*	`conf`	Mitigating Memorization of Noisy Labels by Clipping the Model Prediction. ICML Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li
2023	J	`jnl`	Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity. IEEE Trans. Knowl. Data Eng. Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu
2023	—	`—`	Natural robustness of machine learning in the open world Hongxin Wei
2023	A*	`conf`	On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. NeurIPS Renchunzi Xie, Hongxin Wei, Lei Feng, Yuzhou Cao, Bo An
2023	J	`jnl`	On the Importance of Feature Separability in Predicting Out-Of-Distribution Error. CoRR Renchunzi Xie, Hongxin Wei, Yuzhou Cao, Lei Feng, Bo An
2023	J	`jnl`	Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition. CoRR Shuoyuan Wang, Jindong Wang, Huajun Xi, Bob Zhang, Lei Zhang, Hongxin Wei
2023	J	`jnl`	Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Shuoyuan Wang, Jindong Wang, Huajun Xi, Bob Zhang, Lei Zhang, Hongxin Wei
2023	A*	`conf`	Regression with Cost-based Rejection. NeurIPS Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng
2023	J	`jnl`	Regression with Cost-based Rejection. CoRR Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng
2023	J	`jnl`	Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks. CoRR Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
2022	A*	`conf`	ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection. NeurIPS Huiping Zhuang, Zhenyu Weng, Hongxin Wei, Renchunzi Xie, Kar-Ann Toh, Zhiping Lin
2022	A*	`conf`	Can Adversarial Training Be Manipulated By Non-Robust Features? NeurIPS Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
2022	J	`jnl`	Can Adversarial Training Be Manipulated By Non-Robust Features? CoRR Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen
2022	A*	`conf`	GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation. AAAI Renchunzi Xie, Hongxin Wei, Lei Feng, Bo An
2022	J	`jnl`	GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation. CoRR Renchunzi Xie, Hongxin Wei, Lei Feng, Bo An
2022	J	`jnl`	Logit Clipping for Robust Learning against Label Noise. CoRR Hongxin Wei, Huiping Zhuang, Renchunzi Xie, Lei Feng, Gang Niu, Bo An, Yixuan Li
2022	A*	`conf`	Mitigating Neural Network Overconfidence with Logit Normalization. ICML Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, Yixuan Li
2022	J	`jnl`	Mitigating Neural Network Overconfidence with Logit Normalization. CoRR Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, Yixuan Li
2022	A*	`conf`	Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets. ICML Hongxin Wei, Lue Tao, Renchunzi Xie, Lei Feng, Bo An
2022	J	`jnl`	Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets. CoRR Hongxin Wei, Lue Tao, Renchunzi Xie, Lei Feng, Bo An
2022	—	`conf`	α-MF Detection Based on Spatial Correlation of Sea Clutter. ICCT Hongxin Wei, Lin Zheng, Chao Yang, Ningyan Wei, Zhenghong Liu
2021	A	`conf`	Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix. BMVC Ziqi Zhang, Yuexiang Li, Hongxin Wei, Kai Ma, Tao Xu, Yefeng Zheng
2021	J	`jnl`	Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix. CoRR Ziqi Zhang, Yuexiang Li, Hongxin Wei, Kai Ma, Tao Xu, Yefeng Zheng
2021	A*	`conf`	Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management. AAAI Rundong Wang, Hongxin Wei, Bo An, Zhouyan Feng, Jun Yao
2021	J	`jnl`	Embedding-Augmented Generalized Matrix Factorization for Recommendation With Implicit Feedback. IEEE Intell. Syst. Lei Feng, Hongxin Wei, Qingyu Guo, Zhuoyi Lin, Bo An
2021	A*	`conf`	Multiple-Instance Learning from Similar and Dissimilar Bags. KDD Lei Feng, Senlin Shu, Yuzhou Cao, Lue Tao, Hongxin Wei, Tao Xiang, Bo An, Gang Niu
2021	A*	`conf`	Open-set Label Noise Can Improve Robustness Against Inherent Label Noise. NeurIPS Hongxin Wei, Lue Tao, Renchunzi Xie, Bo An
2021	J	`jnl`	Open-set Label Noise Can Improve Robustness Against Inherent Label Noise. CoRR Hongxin Wei, Lue Tao, Renchunzi Xie, Bo An
2020	J	`jnl`	5G Embraces Satellites for 6G Ubiquitous IoT: Basic Models for Integrated Satellite Terrestrial Networks. CoRR Xinran Fang, Te Wei, Wei Feng, Hongxin Wei, Yunfei Chen, Ning Ge, Cheng-Xiang Wang
2020	A*	`conf`	Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization. CVPR Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An
2020	J	`jnl`	Combating noisy labels by agreement: A joint training method with co-regularization. CoRR Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An
2020	J	`jnl`	Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management. CoRR Rundong Wang, Hongxin Wei, Bo An, Zhouyan Feng, Jun Yao
2020	J	`jnl`	Creating Efficient Blockchains for the Internet of Things by Coordinated Satellite-Terrestrial Networks. CoRR Hongxin Wei, Wei Feng, Chi Zhang, Yunfei Chen, Yuguang Fang, Ning Ge
2020	J	`jnl`	Creating Efficient Blockchains for the Internet of Things by Coordinated Satellite-Terrestrial Networks. IEEE Wirel. Commun. Hongxin Wei, Wei Feng, Chi Zhang, Yunfei Chen, Yuguang Fang, Ning Ge
2020	J	`jnl`	MetaInfoNet: Learning Task-Guided Information for Sample Reweighting. CoRR Hongxin Wei, Lei Feng, Rundong Wang, Bo An
2020	J	`jnl`	Rethinking Blockchains in the Internet of Things Era from a Wireless Communication Perspective. CoRR Hongxin Wei, Wei Feng, Yunfei Chen, Cheng-Xiang Wang, Ning Ge
2020	J	`jnl`	Rethinking Blockchains in the Internet of Things Era from a Wireless Communication Perspective. IEEE Netw. Hongxin Wei, Wei Feng, Yunfei Chen, Cheng-Xiang Wang, Ning Ge
2018	J	`jnl`	Queue-aware energy-efficient scheduling and power allocation with feedback reduction in small-cell networks. Sci. China Inf. Sci. Hongxin Wei, Yunzhou Li, Limin Xiao, Shidong Zhou
2016	B	`conf`	Queue-aware energy-efficient scheduling and power allocation in small-cell networks with interference. WCNC Hongxin Wei, Limin Xiao, Yunzhou Li, Shidong Zhou
2014	—	`conf`	Feedback Reduction for Queue-aware Coordinated Multi-user Scheduling in Small-cell Networks. MILCOM Hongxin Wei, Xiaofeng Zhong, Ming Zhao, Yang Yan, Shidong Zhou
2014	—	`conf`	Queue-aware energy-efficient scheduling in small-cell networks. ICC Workshops Hongxin Wei, Yang Yan, Limin Xiao, Shidong Zhou