Kai Liu

Orcid: 0000-0002-1272-0262

Affiliations:
  • Colorado School of Mines, Department of Computer Science, Golden, CO, USA


According to our database1, Kai Liu authored at least 11 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A Provable Splitting Approach for Symmetric Nonnegative Matrix Factorization.
IEEE Trans. Knowl. Data Eng., March, 2023

2021
Factor-Bounded Nonnegative Matrix Factorization.
ACM Trans. Knowl. Discov. Data, 2021

2020
Learning Robust Multilabel Sample Specific Distances for Identifying HIV-1 Drug Resistance.
J. Comput. Biol., 2020

2019
Spherical Principal Component Analysis.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Learning Robust Multi-label Sample Specific Distances for Identifying HIV-1 Drug Resistance.
Proceedings of the Research in Computational Molecular Biology, 2019

Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Visual Place Recognition via Robust ℓ2-Norm Distance Based Holism and Landmark Integration.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018


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