2022

• Mingfei Shi*, Kaixun Hua*, Jiayang Ren, Yankai Cao (2022). A Scalable deterministic global optimization algorithm for clustering problems. In International Conference on Machine Learning (pp. 4391-4401). PMLR.
  ICML 2022

• Jiayang Ren*, Kaixun Hua*, Yankai Cao (2022). Global Optimal K-Medoids Clustering of One Million Samples. Advances in Neural Information Processing Systems, 35, 982-994.
  NeurIPS 2022

• Kaixun Hua, Jiayang Ren, Yankai Cao (2022). A Scalable Deterministic Global Optimization Algorithm for Training Optimal Decision Tree. Advances in Neural Information Processing Systems, 35, 8347-8359.
  NeurIPS 2022

• Jiayang Ren, Ningning You, Kaixun Hua, Chaojie Ji, Yankai Cao (2022). A Global Optimization Algorithm for K-Center Clustering of One Billion Samples. arXiv preprint arXiv:2301.00061.
  Under review for Management Science

2021

• Kaixun Hua, Mingfei Shi, Yankai Cao (2021). A Scalable deterministic global optimization algorithm for clustering problems. In International Conference on Machine Learning (pp. 4391-4401). PMLR.
  ICML 2021

2019

• Ziyao Xu, Jijian Lian, Lingling Bin, Kaixun Hua, Kui Xu, Hoi Yi Chan (2019). Water Price Prediction for Increasing Market Efficiency Using Random Forest Regression: A Case Study in the Western United States. Water.
  

• Dan A. Simovici, Kaixun Hua (2019). Data ultrametricity and clusterability. In Journal of Physics: Conference Series (Vol. 1334, No. 1, p. 012002). IOP Publishing.
  

Before 2018

• Kaixun Hua, Dan A. Simovici (2018). Dual Criteria Determination of the Number of Clusters in Data. In 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC ‘18), Timisoara, Romania, pp. 201-208.
  

• Dan A. Simovici, Rosanne Vetro, Kaixun Hua (2017). Ultrametricity of Dissimilarity Spaces and Its Significance for Data Mining In: Guillet F., Pinaud B., Venturini G. (eds) Advances in Knowledge Discovery and Management. Studies in Computational Intelligence, vol 665. Springer, Cham.
  

• Irina Scheffner, Kaixun Hua, Dan Simovici, Tanja Abeling, Hermann G. Haller, & Wilfried Gwinner (2016). Prediction of Patient Survival After Kidney Transplantation: Construction, Validation and Evaluation of Decision Models Using Data Mining Approaches. In American Journal OF Transplantation (Vol. 16, pp. 572-573). 111 River St, Hoboken 07030-5774, NJ USA: WILEY-BLACKWELL.
  

• Kaixun Hua, Dan A. Simovici (2016). Long-lead term precipitation forecasting by hierarchical clustering-based bayesian structural vector autoregression. 2016 IEEE 13th International Conference on Networking, Sensing, and Control (ICNSC ‘16), Mexico City, Mexico, pp. 1-6.