Optimistic Robust Optimization With Applications To Machine Learning. - Matthew Norton 001; Akiko Takeda; Alexander Mafusalov (CoRR, 2017)

Soft Margin Support Vector Classification as Buffered Probability Minimization. - Matthew Norton 001; Alexander Mafusalov; Stan Uryasev (J. Mach. Learn. Res., 2017)

Cardinality of Upper Average and Its Application to Network Optimization. - Matthew Norton 001; Alexander Mafusalov; Stan Uryasev (SIAM J. Optim., 2018)

Generalized Batch Normalization: Towards Accelerating Deep Neural Networks. - Xiaoyong Yuan; Zheng Feng; Matthew Norton 001; Xiaolin Li 001 (AAAI, 2019)

DC Pulsed Load Transient Classification Using Long Short-Term Memory Recurrent Neural Networks. - Damian Oslebo; Keith A. Corzine; Todd R. Weatherford; Atif Maqsood; Matthew Norton 001 (ICSPCS, 2019)

Maximization of AUC and Buffered AUC in binary classification. - Matthew Norton 001; Stan Uryasev (Math. Program., 2019)

Certifiable Risk-Based Engineering Design Optimization. - Anirban Chaudhuri; Boris Kramer; Matthew Norton 001; Johannes O. Royset; Karen Willcox (CoRR, 2021)

Calculating CVaR and bPOE for common probability distributions with application to portfolio optimization and density estimation. - Matthew Norton 001; Valentyn Khokhlov; Stan Uryasev (Ann. Oper. Res., 2021)

Diametrical Risk Minimization: theory and computations. - Matthew D. Norton; Johannes O. Royset (Mach. Learn., 2023)