Large Margin Metric Learning for Multi-Label Prediction

Keywords

Margin (machine learning), Metric (unit), Computer science, Decoding methods, Dependency (UML)

References

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• Learning with Idealized KernelsJames T. Kwok, Ivor W. Tsang — 2003
• Objective-Guided Image AnnotationQi Mao, Ivor W. Tsang, Shenghua Gao — 2013
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• Distance Metric Learning for Large Margin Nearest Neighbor ClassificationKilian Q. Weinberger, Lawrence K. Saul — 2005
• A Review on Multi-Label Learning AlgorithmsMin-Ling Zhang, Zhi‐Hua Zhou — 2014
• An improved GLMNET for l1-regularized logistic regressionGuo-Xun Yuan, Chia-Hua Ho, Chih‐Jen Lin — 2011
• Multi-Label Prediction via Compressed SensingJohn Langford, Tong Zhang, Daniel Hsu — 2009
• Semantic Annotation and Retrieval of Music and Sound EffectsDouglas Turnbull, Luke Barrington, David Torres-Moreno — 2008
• LIBLINEAR: A Library for Large Linear ClassificationRong-En Fan, Kai‐Wei Chang, Cho‐Jui Hsieh — 2008
• Metric Learning: A SurveyBrian Kulis — 2013
• Multi-label learning by exploiting label dependencyMin-Ling Zhang, Kun Zhang — 2010
• Cover trees for nearest neighborAlina Beygelzimer, Sham M. Kakade, John Langford — 2006
• Correlated Label Propagation with Application to Multi-label LearningKang Feng, Rong Jin, Rahul Sukthankar — 2006
• Multi-Label Classification: An OverviewGrigorios Tsoumakas, Ioannis Katakis — 2007
• Learning multi-label scene classificationMatthew Boutell, Jiebo Luo, Xipeng Shen — 2004

Cited by

• On the Optimality of Classifier Chain for Multi-label ClassificationWeiwei Liu, Ivor W. Tsang — 2015
• User Identity Linkage by Latent User Space ModellingXin Mu, Feida Zhu, Ee‐Peng Lim — 2016
• Multi-label classification with feature-aware implicit encoding and generalized cross-entropy lossFatemeh Farahnak-Ghazani, Mahdieh Soleymani Baghshah — 2016
• Scalable large margin online metric learningGuoqiang Zhong, Yan Zheng, Sheng Li — 2016
• Learning with Marginalized Corrupted Features and Labels TogetherYingming Li, Ming Yang, Zenglin Xu — 2016
• Learning Distance Metrics for Multi-Label ClassificationHenry Gouk, Bernhard Pfahringer, Michael J. Cree — 2016
• Collaborative Metric LearningCheng-Kang Hsieh, Longqi Yang, Yin Cui — 2017
• Learning with Feature Network and Label Network SimultaneouslyYingming Li, Ming Yang, Zenglin Xu — 2017
• Compressed K-Means for Large-Scale ClusteringXiaobo Shen, Weiwei Liu, Ivor W. Tsang — 2017
• Improving Pairwise Ranking for Multi-label Image ClassificationYuncheng Li, Yale Song, Jiebo Luo — 2017
• Training DCNN by Combining Max-Margin, Max-Correlation Objectives, and Correntropy Loss for Multilabel Image ClassificationWeiwei Shi, Yihong Gong, Xiaoyu Tao — 2018
• SLMOML: Online Metric Learning With Global ConvergenceGuoqiang Zhong, Yan Zheng, Sheng Li — 2018
• Subset Labeled LDA for Large-Scale Multi-Label ClassificationYannis Papanikolaou, Grigorios Tsoumakas — 2017
• Advanced topics in multi-label learningWeiwei Liu — 2017
• Making Decision Trees Feasible in Ultrahigh Feature and Label DimensionsWeiwei Liu, Ivor W. Tsang — 2017
• Multi-dimensional classification via a metric approachZhongchen Ma, Songcan Chen — 2018
• Kernel method for matrix completion with side information and its application in multi-label learningMiao Xu, Zhi‐Hua Zhou — 2017
• Multilabel Prediction via Cross-View SearchXiaobo Shen, Weiwei Liu, Ivor W. Tsang — 2018
• NMF-Based Label Space Factorization for Multi-label ClassificationMohammad Firouzi, Mahmood Karimian, Mahdieh Soleymani — 2017
• ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendationChuxu Zhang, Lu Yu, Xiangliang Zhang — 2017

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