Qi Mao

According to our database, Qi Mao authored at least 23 papers between 2010 and 2019.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2019

Probabilistic Dimensionality Reduction via Structure Learning.

Li Wang, Qi Mao

IEEE Trans. Pattern Anal. Mach. Intell., 2019

A parallel computational framework for ultra-large-scale sequence clustering analysis.

Wei Zheng, Qi Mao, Robert J. Genco, Jean Wactawski-Wende, Michael Buck, Yunpeng Cai, Yijun Sun

Bioinform., 2019

2017

ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time.

Yunpeng Cai, Wei Zheng, Jin Yao, Yujie Yang, Volker Mai, Qi Mao, Yijun Sun

PLoS Comput. Biol., 2017

Principal Graph and Structure Learning Based on Reversed Graph Embedding.

Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun

IEEE Trans. Pattern Anal. Mach. Intell., 2017

A unified probabilistic framework for robust manifold learning and embedding.

Qi Mao, Li Wang, Ivor W. Tsang

Mach. Learn., 2017

Latent Smooth Skeleton Embedding.

Li Wang, Qi Mao, Ivor W. Tsang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2015

Generalized Multiple Kernel Learning With Data-Dependent Priors.

Qi Mao, Ivor W. Tsang, Shenghua Gao, Li Wang

IEEE Trans. Neural Networks Learn. Syst., 2015

Feature selection for unsupervised learning through local learning.

Jin Yao, Qi Mao, Steve Goodison, Volker Mai, Yijun Sun

Pattern Recognit. Lett., 2015

A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation.

Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun

CoRR, 2015

SimplePPT: A Simple Principal Tree Algorithm.

Qi Mao, Le Yang, Li Wang, Steve Goodison, Yijun Sun

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Dimensionality Reduction Via Graph Structure Learning.

Qi Mao, Li Wang, Steve Goodison, Yijun Sun

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Parallel Hierarchical Clustering in Linearithmic Time for Large-Scale Sequence Analysis.

Qi Mao, Wei Zheng, Li Wang, Yunpeng Cai, Volker Mai, Yijun Sun

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

2013

Structured prediction for feature selection and performance evaluation

Qi Mao

PhD thesis, 2013

Efficient Multitemplate Learning for Structured Prediction.

Qi Mao, Ivor Wai-Hung Tsang

IEEE Trans. Neural Networks Learn. Syst., 2013

Objective-Guided Image Annotation.

Qi Mao, Ivor Wai-Hung Tsang, Shenghua Gao

IEEE Trans. Image Process., 2013

A Feature Selection Method for Multivariate Performance Measures.

Qi Mao, Ivor Wai-Hung Tsang

IEEE Trans. Pattern Anal. Mach. Intell., 2013

2012

Multi-view Positive and Unlabeled Learning.

Joey Tianyi Zhou, Sinno Jialin Pan, Qi Mao, Ivor W. Tsang

Proceedings of the 4th Asian Conference on Machine Learning, 2012

A Split-Merge Framework for Comparing Clusterings.

Qiaoliang Xiang, Qi Mao, Kian Ming Adam Chai, Hai Leong Chieu, Ivor W. Tsang, Zhendong Zhao

Proceedings of the 29th International Conference on Machine Learning, 2012

Learning Target Predictive Function without Target Labels.

Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong, Qi Mao

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Domain Adaptation for Coreference Resolution: An Adaptive Ensemble Approach.

Jian-Bo Yang, Qi Mao, Qiaoliang Xiang, Ivor Wai-Hung Tsang, Kian Ming Adam Chai, Hai Leong Chieu

Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012

2011

Multiple Template Learning for Structured Prediction

Qi Mao, Ivor W. Tsang

CoRR, 2011

Optimizing Performance Measures for Feature Selection.

Qi Mao, Ivor Wai-Hung Tsang

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

Parameter-Free Spectral Kernel Learning.

Qi Mao, Ivor W. Tsang

Proceedings of the UAI 2010, 2010