Min-Ling Zhang

250 papers A* 98A 4B 5C 5Misc 1Journal 125Unranked 8
YearRankTypeTitle / Venue / Authors
2026 A* conf
APVR: Hour-Level Long Video Understanding with Adaptive Pivot Visual Information Retrieval.
AAAI
Hong Gao, Yiming Bao, Xuezhen Tu, Bin Zhong, Linan Yue, Min-Ling Zhang
2026 J jnl
Analytical Survey of Learning with Low-Resource Data: From Analysis to Investigation.
ACM Comput. Surv.
Xiaofeng Cao, Mingwei Xu, Xin Yu, Jiangchao Yao, Wei Ye, Sheng-Jun Huang, Min-Ling Zhang, Ivor W. Tsang, Yew-Soon Ong, James T. Kwok, Heng Tao Shen
2026 J jnl
Bridging Efficiency and Transparency: Explainable CoT Compression in Multimodal Large Reasoning Models.
CoRR
Yizhi Wang, Linan Yue, Min-Ling Zhang
2026 A* conf
Classifier-induced Reciprocal Points for Multi-label Open-set Recognition.
AAAI
Yibo Wang, Yong Rui, Min-Ling Zhang
2026 A* conf
Collaborative Dual Representations for Semi-Supervised Partial Label Learning.
AAAI
Wei-Xuan Bao, Yong Rui, Min-Ling Zhang
2026 J jnl
DC-Merge: Improving Model Merging with Directional Consistency.
CoRR
Han-Chen Zhang, Zi-Hao Zhou, Mao-Lin Luo, Shimin Di, Min-Ling Zhang, Tong Wei
2026 J jnl
Data Augmentation With Regularization for Multi-Labeled Complementary Label Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Yi Gao, Yuan-Yuan Meng, Miao Xu, Min-Ling Zhang
2026 J jnl
Evolutionary Dimension-Specific Feature Selection for Multi-Dimensional Classification.
IEEE Trans. Pattern Anal. Mach. Intell.
Yu-Yang Zhang, Bin-Bin Jia, Min-Ling Zhang
2026 J jnl
Guided by Trajectories: Repairing and Rewarding Tool-Use Trajectories for Tool-Integrated Reasoning.
CoRR
Siyu Gong, Linan Yue, Weibo Gao, Fangzhou Yao, Shimin Di, Lei Feng, Min-Ling Zhang
2026 J jnl
KeepLoRA: Continual Learning with Residual Gradient Adaptation.
CoRR
Mao-Lin Luo, Zi-Hao Zhou, Yi-Lin Zhang, Yuanyu Wan, Tong Wei, Min-Ling Zhang
2026 J jnl
Learning to Compose for Cross-domain Agentic Workflow Generation.
CoRR
Jialiang Wang, Shengxiang Xu, Hanmo Liu, Jiachuan Wang, Yuyu Luo, Shimin Di, Min-Ling Zhang, Lei Chen
2026 J jnl
Partial label learning with semi-supervised clustering disambiguation.
Pattern Recognit.
Jun-Ying Liu, Jian-Ping Sun, Ya-Hong Zhao, Bin-Bin Jia, Min-Ling Zhang
2026 J jnl
PeroMAS: A Multi-agent System of Perovskite Material Discovery.
CoRR
Yishu Wang, Wei Liu, Yifan Li, Shengxiang Xu, Xujie Yuan, Ran Li, Yuyu Luo, Jia Zhu, Shimin Di, Min-Ling Zhang, Guixiang Li
2026 J jnl
Robust long-tailed learning under label noise.
Frontiers Comput. Sci.
Tong Wei, Jiang-Xin Shi, Min-Ling Zhang, Yufeng Li
2026 J jnl
Sci-VLA: Agentic VLA Inference Plugin for Long-Horizon Tasks in Scientific Experiments.
CoRR
Yiwen Pang, Bowen Zhou, Changjin Li, Xuanhao Wang, Shengxiang Xu, Deng-Bao Wang, Min-Ling Zhang, Shimin Di
2026 J jnl
Semi-supervised partial label learning via label confidence recovery.
Pattern Recognit.
Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang
2026 J jnl
Similarity-based multi-dimensional multi-label classification.
Frontiers Comput. Sci.
Zi-Zhan Gu, Bin-Bin Jia, Min-Ling Zhang
2026 J jnl
Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation.
CoRR
Hao Gu, Mao-Lin Luo, Zi-Hao Zhou, Han-Chen Zhang, Min-Ling Zhang, Tong Wei
2026 J jnl
ToolRosetta: Bridging Open-Source Repositories and Large Language Model Agents through Automated Tool Standardization.
CoRR
Shimin Di, Xujie Yuan, Hanghui Guo, Chaoqian Ouyang, Zhangze Chen, Ling Yue, Libin Zheng, Jia Zhu, Shaowu Pan, Jian Yin, Min-Ling Zhang, Yong Rui
2025 J jnl
Adaptive VDI Session Placement via User Logoff Prediction.
Mach. Intell. Res.
Wenping Fan, Puhui Meng, Yu Tian, Min-Ling Zhang, Yao Zhang
2025 J jnl
Agentic Video Intelligence: A Flexible Framework for Advanced Video Exploration and Understanding.
CoRR
Hong Gao, Yiming Bao, Xuezhen Tu, Yutong Xu, Yue Jin, Yiyang Mu, Bin Zhong, Linan Yue, Min-Ling Zhang
2025 J jnl
Calibratable Disambiguation Loss for Multi-Instance Partial-Label Learning.
CoRR
Wei Tang, Yin-Fang Yang, Weijia Zhang, Min-Ling Zhang
2025 J jnl
Code2MCP: Transforming Code Repositories into MCP Services.
CoRR
Chaoqian Ouyang, Ling Yue, Shimin Di, Libin Zheng, Linan Yue, Shaowu Pan, Jian Yin, Min-Ling Zhang
2025 J jnl
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models.
CoRR
Linan Yue, Yichao Du, Yizhi Wang, Weibo Gao, Fangzhou Yao, Li Wang, Ye Liu, Ziyu Xu, Qi Liu, Shimin Di, Min-Ling Zhang
2025 J jnl
Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification.
ACM Trans. Knowl. Discov. Data
Jun-Yi Hang, Min-Ling Zhang
2025 A* conf
Evolutionary Classifier Chain for Multi-Dimensional Classification.
AAAI
Yu-Yang Zhang, Bin-Bin Jia, Min-Ling Zhang
2025 A* conf
Fast Multi-Instance Partial-Label Learning.
AAAI
Yin-Fang Yang, Wei Tang, Min-Ling Zhang
2025 A* conf
Generalization Analysis for Controllable Learning.
ICML
Yifan Zhang, Xiao Zhang, Min-Ling Zhang
2025 A conf
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks.
AISTATS
Xin Liu, Weijia Zhang, Min-Ling Zhang
2025 A* conf
Implicit Relative Labeling-Importance Aware Multi-Label Metric Learning.
AAAI
Junxiang Mao, Yong Rui, Min-Ling Zhang
2025 J jnl
Instance-Specific Loss-Weighted Decoding for Decomposition-Based Multiclass Classification.
IEEE Trans. Neural Networks Learn. Syst.
Bin-Bin Jia, Jun-Ying Liu, Min-Ling Zhang
2025 J jnl
Instance-dependent label noise learning via separating style from content.
Pattern Recognit. Lett.
Han-Wen Deng, Weijia Zhang, Min-Ling Zhang
2025 A* conf
LADA: Scalable Label-Specific CLIP Adapter for Continual Learning.
ICML
Mao-Lin Luo, Zi-Hao Zhou, Tong Wei, Min-Ling Zhang
2025 J jnl
LADA: Scalable Label-Specific CLIP Adapter for Continual Learning.
CoRR
Mao-Lin Luo, Zi-Hao Zhou, Tong Wei, Min-Ling Zhang
2025 A* conf
Learnware Specification via Dual Alignment.
ICML
Wei Chen, Junxiang Mao, Xiaozheng Wang, Min-Ling Zhang
2025 A* conf
Learnware Specification via Label-Aware Neural Embedding.
AAAI
Wei Chen, Junxiang Mao, Min-Ling Zhang
2025 J jnl
MotionDuet: Dual-Conditioned 3D Human Motion Generation with Video-Regularized Text Learning.
CoRR
Yiyang Zhang, Tengjiao Sun, Pengcheng Fang, Deng-Bao Wang, Xiaohao Cai, Min-Ling Zhang, Hansung Kim
2025 J jnl
Multi-Instance Partial-Label Learning with Margin Adjustment.
CoRR
Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2025 J jnl
Multi-Label Learning With Multiple Complementary Labels.
IEEE Trans. Pattern Anal. Mach. Intell.
Yi Gao, Jing-Yi Zhu, Miao Xu, Min-Ling Zhang
2025 A* conf
Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning.
ICLR
Xiaorui Peng, Yuheng Jia, Fuchao Yang, Ran Wang, Min-Ling Zhang
2025 J jnl
OmniGround: A Comprehensive Spatio-Temporal Grounding Benchmark for Real-World Complex Scenarios.
CoRR
Hong Gao, Jingyu Wu, Xiangkai Xu, Kangni Xie, Yunchen Zhang, Bin Zhong, Xurui Gao, Min-Ling Zhang
2025 J jnl
Pairwise statistical comparisons of multiple algorithms.
Frontiers Comput. Sci.
Bin-Bin Jia, Jun-Ying Liu, Min-Ling Zhang
2025 A* conf
Partial Label Causal Representation Learning for Instance-Dependent Supervision and Domain Generalization.
AAAI
Yizhi Wang, Weijia Zhang, Min-Ling Zhang
2025 J jnl
Partial multi-label learning via label-specific feature corrections.
Sci. China Inf. Sci.
Jun-Yi Hang, Min-Ling Zhang
2025 A* conf
Radar-Mamba: 4D Millimeter-Wave Point Cloud Enhancement via State Space Models.
ACM Multimedia
Hong Gao, Xiangkai Xu, Tianqi Zhu, Xiugang Dong, Yiming Bao, Min-Ling Zhang
2025 A* conf
Realistic Evaluation of Deep Partial-Label Learning Algorithms.
ICLR
Wei Wang, Dong-Dong Wu, Jindong Wang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
2025 J jnl
Realistic Evaluation of Deep Partial-Label Learning Algorithms.
CoRR
Wei Wang, Dong-Dong Wu, Jindong Wang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
2025 J jnl
RobustFlow: Towards Robust Agentic Workflow Generation.
CoRR
Shengxiang Xu, Jiayi Zhang, Shimin Di, Yuyu Luo, Liang Yao, Hanmo Liu, Jia Zhu, Fan Liu, Min-Ling Zhang
2025 A* conf
Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency.
ICLR
Kai Gan, Bo Ye, Min-Ling Zhang, Tong Wei
2025 J jnl
Special topic on enabling techniques and cutting-edge applications of foundation models.
Sci. China Inf. Sci.
Liping Jing, Qi Liu, Min-Ling Zhang
2025 A* conf
Tight and Fast Bounds for Multi-Label Learning.
ICML
Yifan Zhang, Min-Ling Zhang
2025 J jnl
Toward Few-Shot Learning in the Open World: A Review and Beyond.
IEEE Trans. Pattern Anal. Mach. Intell.
Hui Xue, Yuexuan An, Yongchun Qin, Wenqian Li, Yixin Wu, Yongjuan Che, Pengfei Fang, Min-Ling Zhang
2025 A* conf
Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification.
ICML
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
2025 J jnl
Training Multimodal Large Reasoning Models Needs Better Thoughts: A Three-Stage Framework for Long Chain-of-Thought Synthesis and Selection.
CoRR
Yizhi Wang, Linan Yue, Min-Ling Zhang
2025 J jnl
Tuning the Right Foundation Models is What you Need for Partial Label Learning.
CoRR
Kuang He, Wei Tang, Tong Wei, Min-Ling Zhang
2025 J jnl
Unleashing the Power of Vision-Language Models for Long-Tailed Multi-Label Visual Recognition.
CoRR
Wei Tang, Zuo-Zheng Wang, Kun Zhang, Tong Wei, Min-Ling Zhang
2025 A* conf
Weakly-Supervised Contrastive Learning for Imprecise Class Labels.
ICML
Zi-Hao Zhou, Junjie Wang, Tong Wei, Min-Ling Zhang
2025 J jnl
Weakly-Supervised Contrastive Learning for Imprecise Class Labels.
CoRR
Zi-Hao Zhou, Junjie Wang, Tong Wei, Min-Ling Zhang
2025 J jnl
What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models?
CoRR
Ming-Kun Xie, Jiahao Xiao, Gang Niu, Lei Feng, Zhiqiang Kou, Min-Ling Zhang, Masashi Sugiyama
2025 A* conf
Wrapped Partial Label Dimensionality Reduction via Dependence Maximization.
IJCAI
Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang
2025 — conf
ZzzMate: A Self-Conscious Emotion-Aware Chatbot for Sleep Intervention.
CHI Extended Abstracts
Xiao Tang, Zhuying Li, Xin Sun, Xuhai Xu, Min-Ling Zhang
2024 J jnl
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification.
CoRR
Xin Liu, Weijia Zhang, Min-Ling Zhang
2024 A* conf
Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning.
ICML
Jun-Yi Hang, Min-Ling Zhang
2024 J jnl
Boosting Consistency in Dual Training for Long-Tailed Semi-Supervised Learning.
CoRR
Kai Gan, Tong Wei, Min-Ling Zhang
2024 A* conf
Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning.
IJCAI
Bo Ye, Kai Gan, Tong Wei, Min-Ling Zhang
2024 A* conf
Calibration Bottleneck: Over-compressed Representations are Less Calibratable.
ICML
Deng-Bao Wang, Min-Ling Zhang
2024 J jnl
Complementary to Multiple Labels: A Correlation-Aware Correction Approach.
IEEE Trans. Pattern Anal. Mach. Intell.
Yi Gao, Miao Xu, Min-Ling Zhang
2024 A* conf
Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition.
NeurIPS
Zi-Hao Zhou, Siyuan Fang, Zi-Jing Zhou, Tong Wei, Yuanyu Wan, Min-Ling Zhang
2024 J jnl
Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition.
CoRR
Zi-Hao Zhou, Siyuan Fang, Zi-Jing Zhou, Tong Wei, Yuanyu Wan, Min-Ling Zhang
2024 A* conf
Deep Multi-Dimensional Classification with Pairwise Dimension-Specific Features.
IJCAI
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
2024 J jnl
Dimensionality Reduction for Partial Label Learning: A Unified and Adaptive Approach.
IEEE Trans. Knowl. Data Eng.
Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang
2024 A* conf
Disentangled Partial Label Learning.
AAAI
Wei-Xuan Bao, Yong Rui, Min-Ling Zhang
2024 A* conf
Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning.
AAAI
Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang
2024 A* conf
EAT: Towards Long-Tailed Out-of-Distribution Detection.
AAAI
Tong Wei, Bo-Lin Wang, Min-Ling Zhang
2024 A* conf
Efficient Model Stealing Defense with Noise Transition Matrix.
CVPR
Dong-Dong Wu, Chilin Fu, Weichang Wu, Wenwen Xia, Xiaolu Zhang, Jun Zhou, Min-Ling Zhang
2024 A* conf
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning.
IJCAI
Wei Tang, Weijia Zhang, Min-Ling Zhang
2024 J jnl
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning.
CoRR
Wei Tang, Weijia Zhang, Min-Ling Zhang
2024 A* conf
Generalization Analysis for Label-Specific Representation Learning.
NeurIPS
Yifan Zhang, Min-Ling Zhang
2024 A* conf
Generalization Analysis for Multi-Label Learning.
ICML
Yifan Zhang, Min-Ling Zhang
2024 J jnl
HACSurv: A Hierarchical Copula-based Approach for Survival Analysis with Dependent Competing Risks.
CoRR
Xin Liu, Weijia Zhang, Min-Ling Zhang
2024 A* conf
Improved Weighted Tensor Schatten
ACM Multimedia
Yinghui Sun, Xingfeng Li, Quansen Sun, Min-Ling Zhang, Zhenwen Ren
2024 J jnl
Label-Specific Time-Frequency Energy-Based Neural Network for Instrument Recognition.
IEEE Trans. Cybern.
Jian Zhang, Tong Wei, Min-Ling Zhang
2024 J jnl
Learning From Noisy Labels via Dynamic Loss Thresholding.
IEEE Trans. Knowl. Data Eng.
Hao Yang, Youzhi Jin, Ziyin Li, Deng-Bao Wang, Xin Geng, Min-Ling Zhang
2024 A* conf
Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition.
ICML
Tong Wei, Zhen Mao, Zi-Hao Zhou, Yuanyu Wan, Min-Ling Zhang
2024 A* conf
Learning Label-Specific Multiple Local Metrics for Multi-Label Classification.
IJCAI
Junxiang Mao, Jun-Yi Hang, Min-Ling Zhang
2024 A* conf
Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation.
AAAI
Yuheng Jia, Xiaorui Peng, Ran Wang, Min-Ling Zhang
2024 A* conf
Multi-Instance Partial-Label Learning with Margin Adjustment.
NeurIPS
Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2024 J jnl
Multi-Label Classification With High-Rank and High-Order Label Correlations.
IEEE Trans. Knowl. Data Eng.
Chongjie Si, Yuheng Jia, Ran Wang, Min-Ling Zhang, Yanghe Feng, Chongxiao Qu
2024 A* conf
Multi-Label Open Set Recognition.
NeurIPS
Yibo Wang, Jun-Yi Hang, Min-Ling Zhang
2024 J jnl
Multi-instance partial-label learning: towards exploiting dual inexact supervision.
Sci. China Inf. Sci.
Wei Tang, Weijia Zhang, Min-Ling Zhang
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
PROMIPL: A Probabilistic Generative Model for Multi-Instance Partial-Label Learning.
ICDM
Yin-Fang Yang, Wei Tang, Min-Ling Zhang
2024 J jnl
Partial label learning with emerging new labels.
Mach. Learn.
Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang
2024 A conf
Proposal Feature Learning Using Proposal Relations for Weakly Supervised Object Detection.
ICME
Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2024 J jnl
Student Loss: Towards the Probability Assumption in Inaccurate Supervision.
IEEE Trans. Pattern Anal. Mach. Intell.
Shuo Zhang, Jianqing Li, Hamido Fujita, Yu-Wen Li, Deng-Bao Wang, Tingting Zhu, Min-Ling Zhang, Chengyu Liu
2024 J jnl
Temporal segment dropout for human action video recognition.
Pattern Recognit.
Yu Zhang, Zhengjie Chen, Tianyu Xu, Junjie Zhao, Siya Mi, Xin Geng, Min-Ling Zhang
2024 J jnl
Towards exploiting linear regression for multi-class/multi-label classification: an empirical analysis.
Int. J. Mach. Learn. Cybern.
Bin-Bin Jia, Jun-Ying Liu, Min-Ling Zhang
2024 A* conf
Unlearning from Weakly Supervised Learning.
IJCAI
Yi Tang, Yi Gao, Yonggang Luo, Jucheng Yang, Miao Xu, Min-Ling Zhang
2024 J jnl
Variational Label Enhancement for Instance-Dependent Partial Label Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Ning Xu, Congyu Qiao, Yuchen Zhao, Xin Geng, Min-Ling Zhang
2024 A* conf
Vision-Language Models are Strong Noisy Label Detectors.
NeurIPS
Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang
2024 J jnl
Vision-Language Models are Strong Noisy Label Detectors.
CoRR
Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang
2024 A* conf
What Makes Partial-Label Learning Algorithms Effective?
NeurIPS
Jiaqi Lv, Yangfan Liu, Shiyu Xia, Ning Xu, Miao Xu, Gang Niu, Min-Ling Zhang, Masashi Sugiyama, Xin Geng
2023 A* conf
Binary Classification with Confidence Difference.
NeurIPS
Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
2023 J jnl
Binary Classification with Confidence Difference.
CoRR
Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
2023 J jnl
Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning.
CoRR
Bo Ye, Kai Gan, Tong Wei, Min-Ling Zhang
2023 A* conf
Can Label-Specific Features Help Partial-Label Learning?
AAAI
Ruo-Jing Dong, Jun-Yi Hang, Tong Wei, Min-Ling Zhang
2023 A* conf
Complementary Classifier Induced Partial Label Learning.
KDD
Yuheng Jia, Chongjie Si, Min-Ling Zhang
2023 J jnl
Complementary Classifier Induced Partial Label Learning.
CoRR
Yuheng Jia, Chongjie Si, Min-Ling Zhang
2023 J jnl
Complementary to Multiple Labels: A Correlation-Aware Correction Approach.
CoRR
Yi Gao, Miao Xu, Min-Ling Zhang
2023 A* conf
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning.
NeurIPS
Wei Tang, Weijia Zhang, Min-Ling Zhang
2023 J jnl
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning.
CoRR
Wei Tang, Weijia Zhang, Min-Ling Zhang
2023 J jnl
EAT: Towards Long-Tailed Out-of-Distribution Detection.
CoRR
Tong Wei, Bo-Lin Wang, Min-Ling Zhang
2023 A* conf
Label Specific Multi-Semantics Metric Learning for Multi-Label Classification: Global Consideration Helps.
IJCAI
Junxiang Mao, Wei Wang, Min-Ling Zhang
2023 J jnl
Learning label-specific features for decomposition-based multi-class classification.
Frontiers Comput. Sci.
Bin-Bin Jia, Jun-Ying Liu, Jun-Yi Hang, Min-Ling Zhang
2023 J jnl
Multi-Dimensional Classification via Decomposed Label Encoding.
IEEE Trans. Knowl. Data Eng.
Bin-Bin Jia, Min-Ling Zhang
2023 J jnl
Multi-dimensional multi-label classification: Towards encompassing heterogeneous label spaces and multi-label annotations.
Pattern Recognit.
Bin-Bin Jia, Min-Ling Zhang
2023 A* conf
Nearly-tight Bounds for Deep Kernel Learning.
ICML
Yifan Zhang, Min-Ling Zhang
2023 A* conf
On the Pitfall of Mixup for Uncertainty Calibration.
CVPR
Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang
2023 A* conf
Partial Multi-Label Learning with Probabilistic Graphical Disambiguation.
NeurIPS
Jun-Yi Hang, Min-Ling Zhang
2023 A* conf
Partial-Label Regression.
AAAI
Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An
2023 J jnl
Partial-Label Regression.
CoRR
Xin Cheng, Deng-Bao Wang, Lei Feng, Min-Ling Zhang, Bo An
2023 A* conf
Progressive Label Propagation for Semi-Supervised Multi-Dimensional Classification.
IJCAI
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
2023 J jnl
Rethinking the Value of Labels for Instance-Dependent Label Noise Learning.
CoRR
Hanwen Deng, Weijia Zhang, Min-Ling Zhang
2023 J jnl
Robust Representation Learning for Unreliable Partial Label Learning.
CoRR
Yu Shi, Dong-Dong Wu, Xin Geng, Min-Ling Zhang
2023 A* conf
Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels.
IJCAI
Hao-Tian Li, Tong Wei, Hao Yang, Kun Hu, Chong Peng, Li-Bo Sun, Xun-Liang Cai, Min-Ling Zhang
2023 J jnl
Towards Enabling Binary Decomposition for Partial Multi-Label Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Bing-Qing Liu, Bin-Bin Jia, Min-Ling Zhang
2023 J jnl
Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection.
CoRR
Zhaofei Wang, Weijia Zhang, Min-Ling Zhang
2023 A* conf
Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning.
IJCAI
Yi Gao, Miao Xu, Min-Ling Zhang
2023 J jnl
Variational Label Enhancement.
IEEE Trans. Pattern Anal. Mach. Intell.
Ning Xu, Jun Shu, RenYi Zheng, Xin Geng, Deyu Meng, Min-Ling Zhang
2022 — conf
(Re-)connecting with Nature in Urban Life: Engaging with Wildlife via AI-powered Wearables.
MobileHCI (Adjunct)
Zhuying Li, Si Cheng, Wei Wang, Min-Ling Zhang
2022 J jnl
A Survey on Extreme Multi-label Learning.
CoRR
Tong Wei, Zhen Mao, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang
2022 J jnl
Adaptive Graph Guided Disambiguation for Partial Label Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Deng-Bao Wang, Min-Ling Zhang, Li Li
2022 J jnl
BiLabel-Specific Features for Multi-Label Classification.
ACM Trans. Knowl. Discov. Data
Min-Ling Zhang, Jun-Peng Fang, Yibo Wang
2022 J jnl
CAFE and SOUP: Toward Adaptive VDI Workload Prediction.
ACM Trans. Intell. Syst. Technol.
Yao Zhang, Wenping Fan, Qichen Hao, Xinya Wu, Min-Ling Zhang
2022 J jnl
Collaborative Learning of Label Semantics and Deep Label-Specific Features for Multi-Label Classification.
IEEE Trans. Pattern Anal. Mach. Intell.
Jun-Yi Hang, Min-Ling Zhang
2022 J jnl
Decomposition-Based Classifier Chains for Multi-Dimensional Classification.
IEEE Trans. Artif. Intell.
Bin-Bin Jia, Min-Ling Zhang
2022 J jnl
Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction.
ACM Trans. Knowl. Discov. Data
Min-Ling Zhang, Jing-Han Wu, Wei-Xuan Bao
2022 A* conf
Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification.
ICML
Jun-Yi Hang, Min-Ling Zhang
2022 A* conf
End-to-End Probabilistic Label-Specific Feature Learning for Multi-Label Classification.
AAAI
Jun-Yi Hang, Min-Ling Zhang, Yanghe Feng, Xiaocheng Song
2022 J jnl
Maximum Margin Multi-Dimensional Classification.
IEEE Trans. Neural Networks Learn. Syst.
Bin-Bin Jia, Min-Ling Zhang
2022 A* conf
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization.
NeurIPS
Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang
2022 J jnl
Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision.
CoRR
Wei Tang, Weijia Zhang, Min-Ling Zhang
2022 J jnl
Multi-Label Classification With Label-Specific Feature Generation: A Wrapped Approach.
IEEE Trans. Pattern Anal. Mach. Intell.
Ze-Bang Yu, Min-Ling Zhang
2022 J jnl
Multi-dimensional Classification via Selective Feature Augmentation.
Int. J. Autom. Comput.
Bin-Bin Jia, Min-Ling Zhang
2022 J jnl
Multi-label Classification with High-rank and High-order Label Correlations.
CoRR
Chongjie Si, Yuheng Jia, Ran Wang, Min-Ling Zhang, Yanghe Feng, Chongxiao Qu
2022 A* conf
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement.
NeurIPS
Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang
2022 J jnl
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement.
CoRR
Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang
2022 A* conf
Partial Label Learning with Discrimination Augmentation.
KDD
Wei Wang, Min-Ling Zhang
2022 — conf
Partial Label Learning with Gradually Induced Error-Correction Output Codes.
ICONIP (1)
Yu-Xuan Shi, Deng-Bao Wang, Min-Ling Zhang
2022 J jnl
Preface.
J. Comput. Sci. Technol.
Min-Ling Zhang, Xiu-Shen Wei, Gao Huang
2022 — conf
Prototypical Classifier for Robust Class-Imbalanced Learning.
PAKDD (2)
Tong Wei, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang
2022 A* conf
Revisiting Consistency Regularization for Deep Partial Label Learning.
ICML
Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang
2022 J jnl
Stable Label-Specific Features Generation for Multi-Label Learning via Mixture-Based Clustering Ensemble.
IEEE CAA J. Autom. Sinica
Yibo Wang, Jun-Yi Hang, Min-Ling Zhang
2022 A* conf
Submodular Feature Selection for Partial Label Learning.
KDD
Wei-Xuan Bao, Jun-Yi Hang, Min-Ling Zhang
2022 J jnl
Towards Class-Imbalance Aware Multi-Label Learning.
IEEE Trans. Cybern.
Min-Ling Zhang, Yu-Kun Li, Hao Yang, Xu-Ying Liu
2022 J jnl
Towards Learning Causal Representations from Multi-Instance Bags.
CoRR
Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang
2021 A* conf
BAMBOO: A Multi-instance Multi-label Approach Towards VDI User Logon Behavior Modeling.
IJCAI
Wen-Ping Fan, Yao Zhang, Qichen Hao, Xinya Wu, Min-Ling Zhang
2021 J jnl
Compositional metric learning for multi-label classification.
Frontiers Comput. Sci.
Yan-Ping Sun, Min-Ling Zhang
2021 A* conf
Correlation-Guided Representation for Multi-Label Text Classification.
IJCAI
Qian-Wen Zhang, Ximing Zhang, Zhao Yan, Ruifang Liu, Yunbo Cao, Min-Ling Zhang
2021 A* conf
Discriminative Complementary-Label Learning with Weighted Loss.
ICML
Yi Gao, Min-Ling Zhang
2021 A* conf
Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning.
AAAI
Zhen-Ru Zhang, Qian-Wen Zhang, Yunbo Cao, Min-Ling Zhang
2021 A* conf
Instance-Dependent Partial Label Learning.
NeurIPS
Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang
2021 J jnl
Instance-Dependent Partial Label Learning.
CoRR
Ning Xu, Congyu Qiao, Xin Geng, Min-Ling Zhang
2021 A* conf
Learning from Complementary Labels via Partial-Output Consistency Regularization.
IJCAI
Deng-Bao Wang, Lei Feng, Min-Ling Zhang
2021 J jnl
Learning from Noisy Labels via Dynamic Loss Thresholding.
CoRR
Hao Yang, Youzhi Jin, Ziyin Li, Deng-Bao Wang, Lei Miao, Xin Geng, Min-Ling Zhang
2021 A* conf
Learning from Noisy Labels with Complementary Loss Functions.
AAAI
Deng-Bao Wang, Yong Wen, Lujia Pan, Min-Ling Zhang
2021 J jnl
Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-Label Learning.
IEEE Trans. Knowl. Data Eng.
Min-Ling Zhang, Qian-Wen Zhang, Jun-Peng Fang, Yu-Kun Li, Xin Geng
2021 A* conf
Multi-Dimensional Classification via Sparse Label Encoding.
ICML
Bin-Bin Jia, Min-Ling Zhang
2021 A* conf
Partial Label Dimensionality Reduction via Confidence-Based Dependence Maximization.
KDD
Wei-Xuan Bao, Jun-Yi Hang, Min-Ling Zhang
2021 J jnl
Partial Multi-Label Learning via Credible Label Elicitation.
IEEE Trans. Pattern Anal. Mach. Intell.
Min-Ling Zhang, Jun-Peng Fang
2021 J jnl
Preface.
J. Comput. Sci. Technol.
Min-Ling Zhang, Sheng-Jun Huang, Mingsheng Long
2021 J jnl
Prototypical Classifier for Robust Class-Imbalanced Learning.
CoRR
Tong Wei, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang
2021 A* conf
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence.
NeurIPS
Deng-Bao Wang, Lei Feng, Min-Ling Zhang
2021 A* conf
Tac-Valuer: Knowledge-based Stroke Evaluation in Table Tennis.
KDD
Jiachen Wang, Dazhen Deng, Xiao Xie, Xinhuan Shu, Yu-Xuan Huang, Le-Wen Cai, Hui Zhang, Min-Ling Zhang, Zhi-Hua Zhou, Yingcai Wu
2020 A* conf
Feature-Induced Manifold Disambiguation for Multi-View Partial Multi-label Learning.
KDD
Jing-Han Wu, Xuan Wu, Qing-Guo Chen, Yao Hu, Min-Ling Zhang
2020 J jnl
Large-scale multi-label classification using unknown streaming images.
Pattern Recognit.
Yu Zhang, Yin Wang, Xu-Ying Liu, Siya Mi, Min-Ling Zhang
2020 A* conf
Maximum Margin Multi-Dimensional Classification.
AAAI
Bin-Bin Jia, Min-Ling Zhang
2020 B conf
Md-knn: An Instance-based Approach for Multi-Dimensional Classification.
ICPR
Bin-Bin Jia, Min-Ling Zhang
2020 A* conf
Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation.
AAAI
Ze-Sen Chen, Xuan Wu, Qing-Guo Chen, Yao Hu, Min-Ling Zhang
2020 J jnl
Multi-dimensional classification via
Pattern Recognit.
Bin-Bin Jia, Min-Ling Zhang
2020 J jnl
Multi-dimensional classification via stacked dependency exploitation.
Sci. China Inf. Sci.
Bin-Bin Jia, Min-Ling Zhang
2020 J jnl
Preface.
J. Comput. Sci. Technol.
Min-Ling Zhang, Yufeng Li, Qi Liu
2020 A* conf
Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization.
NeurIPS
Wei Wang, Min-Ling Zhang
2019 A* conf
Adaptive Graph Guided Disambiguation for Partial Label Learning.
KDD
Deng-Bao Wang, Li Li, Min-Ling Zhang
2019 — ed.
Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part I
PAKDD (1)
Qiang Yang, Zhi-Hua Zhou, Zhiguo Gong, Min-Ling Zhang, Sheng-Jun Huang
2019 — ed.
Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part II
PAKDD (2)
Qiang Yang, Zhi-Hua Zhou, Zhiguo Gong, Min-Ling Zhang, Sheng-Jun Huang
2019 — ed.
Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Macau, China, April 14-17, 2019, Proceedings, Part III
PAKDD (3)
Qiang Yang, Zhi-Hua Zhou, Zhiguo Gong, Min-Ling Zhang, Sheng-Jun Huang
2019 A* conf
CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features.
AAAI
Yao Zhang, Wen-Ping Fan, Xuan Wu, Hua Chen, Bin-Yang Li, Min-Ling Zhang
2019 A* conf
Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction.
KDD
Jing-Han Wu, Min-Ling Zhang
2019 A* conf
Multi-Dimensional Classification via kNN Feature Augmentation.
AAAI
Bin-Bin Jia, Min-Ling Zhang
2019 C conf
Multi-Label Learning with Regularization Enriched Label-Specific Features.
ACML
Ze-Sen Chen, Min-Ling Zhang
2019 A* conf
Multi-View Multi-Label Learning with View-Specific Information Extraction.
IJCAI
Xuan Wu, Qing-Guo Chen, Yao Hu, Dengbao Wang, Xiaodong Chang, Xiaobo Wang, Min-Ling Zhang
2019 J jnl
Neighborhood kinship preserving hashing for supervised learning.
Signal Process. Image Commun.
Yan Cui, Jielin Jiang, Zuojin Hu, Xiaoyan Jiang, Wuxia Yan, Min-Ling Zhang
2019 A* conf
Partial Multi-Label Learning via Credible Label Elicitation.
AAAI
Jun-Peng Fang, Min-Ling Zhang
2019 J jnl
Supervised representation learning for multi-label classification.
Mach. Learn.
Ming Huang, Fuzhen Zhuang, Xiao Zhang, Xiang Ao, Zhengyu Niu, Min-Ling Zhang, Qing He
2019 J jnl
Transfer synthetic over-sampling for class-imbalance learning with limited minority class data.
Frontiers Comput. Sci.
Xu-Ying Liu, Sheng-Tao Wang, Min-Ling Zhang
2018 A conf
A new R2 indicator for better hypervolume approximation.
GECCO
Ke Shang, Hisao Ishibuchi, Min-Ling Zhang, Yiping Liu
2018 J jnl
Binary relevance for multi-label learning: an overview.
Frontiers Comput. Sci.
Min-Ling Zhang, Yu-Kun Li, Xu-Ying Liu, Xin Geng
2018 A* conf
Feature-Induced Labeling Information Enrichment for Multi-Label Learning.
AAAI
Qian-Wen Zhang, Yun Zhong, Min-Ling Zhang
2018 A* conf
Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence Propagation.
ICDM
Si-Yu Ding, Xu-Ying Liu, Min-Ling Zhang
2018 A* conf
Towards Enabling Binary Decomposition for Partial Label Learning.
IJCAI
Xuan Wu, Min-Ling Zhang
2018 A* conf
Towards Mitigating the Class-Imbalance Problem for Partial Label Learning.
KDD
Jing Wang, Min-Ling Zhang
2018 J jnl
Weakly Supervised POS Tagging without Disambiguation.
ACM Trans. Asian Low Resour. Lang. Inf. Process.
Deyu Zhou, Zhikai Zhang, Min-Ling Zhang, Yulan He
2017 A* conf
Binary Linear Compression for Multi-label Classification.
IJCAI
Wen-Ji Zhou, Yang Yu, Min-Ling Zhang
2017 A* conf
Confidence-Rated Discriminative Partial Label Learning.
AAAI
Cai-Zhi Tang, Min-Ling Zhang
2017 J jnl
Disambiguation-Free Partial Label Learning.
IEEE Trans. Knowl. Data Eng.
Min-Ling Zhang, Fei Yu, Cai-Zhi Tang
2017 A* conf
Inductive Semi-supervised Multi-Label Learning with Co-Training.
KDD
Wang Zhan, Min-Ling Zhang
2017 C ed.
Intelligent Data Engineering and Automated Learning - IDEAL 2017 - 18th International Conference, Guilin, China, October 30 - November 1, 2017, Proceedings
IDEAL
Hujun Yin, Yang Gao, Songcan Chen, Yimin Wen, Guoyong Cai, Tianlong Gu, Junping Du, Antonio J. Tallón-Ballesteros, Min-Ling Zhang
2017 J jnl
Maximum margin partial label learning.
Mach. Learn.
Fei Yu, Min-Ling Zhang
2017 B conf
Multi-label Learning with Label-Specific Features via Clustering Ensemble.
DSAA
Wang Zhan, Min-Ling Zhang
2017 — ch.
Multi-label Learning.
Encyclopedia of Machine Learning and Data Mining
Zhi-Hua Zhou, Min-Ling Zhang
2017 C ed.
Proceedings of The 9th Asian Conference on Machine Learning, ACML 2017, Seoul, Korea, November 15-17, 2017.
ACML
Min-Ling Zhang, Yung-Kyun Noh
2016 A* conf
Multi-Label Manifold Learning.
AAAI
Peng Hou, Xin Geng, Min-Ling Zhang
2016 B ed.
PRICAI 2016: Trends in Artificial Intelligence - 14th Pacific Rim International Conference on Artificial Intelligence, Phuket, Thailand, August 22-26, 2016, Proceedings
PRICAI
Richard Booth, Min-Ling Zhang
2016 A* conf
Partial Label Learning via Feature-Aware Disambiguation.
KDD
Min-Ling Zhang, Bin-Bin Zhou, Xu-Ying Liu
2015 A* conf
Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-label Learning.
ICDM
Yu-Kun Li, Min-Ling Zhang, Xin Geng
2015 J jnl
Lift: Multi-Label Learning with Label-Specific Features.
IEEE Trans. Pattern Anal. Mach. Intell.
Min-Ling Zhang, Lei Wu
2015 C conf
Maximum Margin Partial Label Learning.
ACML
Fei Yu, Min-Ling Zhang
2015 A* conf
Solving the Partial Label Learning Problem: An Instance-Based Approach.
IJCAI
Min-Ling Zhang, Fei Yu
2015 A* conf
Towards Class-Imbalance Aware Multi-Label Learning.
IJCAI
Min-Ling Zhang, Yu-Kun Li, Xu-Ying Liu
2014 J jnl
A Review on Multi-Label Learning Algorithms.
IEEE Trans. Knowl. Data Eng.
Min-Ling Zhang, Zhi-Hua Zhou
2014 A conf
Disambiguation-Free Partial Label Learning.
SDM
Min-Ling Zhang
2014 B conf
Enhancing Binary Relevance for Multi-label Learning with Controlled Label Correlations Exploitation.
PRICAI
Yu-Kun Li, Min-Ling Zhang
2013 J jnl
Exploiting unlabeled data to enhance ensemble diversity.
Data Min. Knowl. Discov.
Min-Ling Zhang, Zhi-Hua Zhou
2013 C conf
Multi-Label Classification with Unlabeled Data: An Inductive Approach.
ACML
Le Wu, Min-Ling Zhang
2012 J jnl
Introduction to the special issue on learning from multi-label data.
Mach. Learn.
Grigorios Tsoumakas, Min-Ling Zhang, Zhi-Hua Zhou
2012 J jnl
Multi-instance multi-label learning.
Artif. Intell.
Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, Yufeng Li
2011 J jnl
CoTrade: Confident Co-Training With Data Editing.
IEEE Trans. Syst. Man Cybern. Part B
Min-Ling Zhang, Zhi-Hua Zhou
2011 A* conf
LIFT: Multi-Label Learning with Label-Specific Features.
IJCAI
Min-Ling Zhang
2010 — conf
A k-Nearest Neighbor Based Multi-Instance Multi-Label Learning Algorithm.
ICTAI (2)
Min-Ling Zhang
2010 A* conf
Exploiting Unlabeled Data to Enhance Ensemble Diversity.
ICDM
Min-Ling Zhang, Zhi-Hua Zhou
2010 A* conf
Multi-label learning by exploiting label dependency.
KDD
Min-Ling Zhang, Kun Zhang
2009 J jnl
Classifier Ensemble with Unlabeled Data
CoRR
Min-Ling Zhang, Zhi-Hua Zhou
2009 J jnl
Feature selection for multi-label naive Bayes classification.
Inf. Sci.
Min-Ling Zhang, José María Peña Sánchez, Víctor Robles
2009 J jnl
MIMLRBF: RBF neural networks for multi-instance multi-label learning.
Neurocomputing
Min-Ling Zhang, Zhijian Wang
2009 J jnl
Ml-rbf : RBF Neural Networks for Multi-Label Learning.
Neural Process. Lett.
Min-Ling Zhang
2009 J jnl
Multi-instance clustering with applications to multi-instance prediction.
Appl. Intell.
Min-Ling Zhang, Zhi-Hua Zhou
2008 A* conf
M3MIML: A Maximum Margin Method for Multi-instance Multi-label Learning.
ICDM
Min-Ling Zhang, Zhi-Hua Zhou
2008 J jnl
MIML: A Framework for Learning with Ambiguous Objects
CoRR
Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, Yufeng Li
2007 J jnl
ML-KNN: A lazy learning approach to multi-label learning.
Pattern Recognit.
Min-Ling Zhang, Zhi-Hua Zhou
2007 A* conf
Multi-Label Learning by Instance Differentiation.
AAAI
Min-Ling Zhang, Zhi-Hua Zhou
2007 J jnl
Solving multi-instance problems with classifier ensemble based on constructive clustering.
Knowl. Inf. Syst.
Zhi-Hua Zhou, Min-Ling Zhang
2006 J jnl
Adapting RBF Neural Networks to Multi-Instance Learning.
Neural Process. Lett.
Min-Ling Zhang, Zhi-Hua Zhou
2006 — conf
Multi-Instance Multi-Label Learning with Application to Scene Classification.
NIPS
Zhi-Hua Zhou, Min-Ling Zhang
2006 J jnl
Multi-Label Neural Networks with Applications to Functional Genomics and Text Categorization.
IEEE Trans. Knowl. Data Eng.
Min-Ling Zhang, Zhi-Hua Zhou
2005 Misc conf
A k-nearest neighbor based algorithm for multi-label classification.
GrC
Min-Ling Zhang, Zhi-Hua Zhou
2004 — conf
Ensembles of Multi-Instance Neural Networks.
IIP
Min-Ling Zhang, Zhi-Hua Zhou
2004 J jnl
Improve Multi-Instance Neural Networks through Feature Selection.
Neural Process. Lett.
Min-Ling Zhang, Zhi-Hua Zhou
2003 B conf
A Novel Bag Generator for Image Database Retrieval With Multi-Instance Learning Techniques.
ICTAI
Zhi-Hua Zhou, Min-Ling Zhang, Ke-Jia Chen
2003 — conf
Ensembles of Multi-instance Learners.
ECML
Zhi-Hua Zhou, Min-Ling Zhang