Matthew Norton

11 papers A* 1Journal 9Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Error control and Neyman-Pearson classification with buffered probability and support vectors.
Comput. Optim. Appl.
Matthew Norton, Liting Chiang, Stan Uryasev
2021 J jnl
Calculating CVaR and bPOE for common probability distributions with application to portfolio optimization and density estimation.
Ann. Oper. Res.
Matthew Norton, Valentyn Khokhlov, Stan Uryasev
2021 J jnl
Certifiable Risk-Based Engineering Design Optimization.
CoRR
Anirban Chaudhuri, Boris Kramer, Matthew Norton, Johannes O. Royset, Karen Willcox
2019 — conf
DC Pulsed Load Transient Classification Using Long Short-Term Memory Recurrent Neural Networks.
ICSPCS
Damian Oslebo, Keith A. Corzine, Todd R. Weatherford, Atif Maqsood, Matthew Norton
2019 J jnl
Diametrical Risk Minimization: Theory and Computations.
CoRR
Matthew Norton, Johannes O. Royset
2019 A* conf
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks.
AAAI
Xiaoyong Yuan, Zheng Feng, Matthew Norton, Xiaolin Li
2019 J jnl
Maximization of AUC and Buffered AUC in binary classification.
Math. Program.
Matthew Norton, Stan Uryasev
2018 J jnl
Cardinality of Upper Average and Its Application to Network Optimization.
SIAM J. Optim.
Matthew Norton, Alexander Mafusalov, Stan Uryasev
2018 J jnl
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks.
CoRR
Xiaoyong Yuan, Zheng Feng, Matthew Norton, Xiaolin Li
2017 J jnl
Optimistic Robust Optimization With Applications To Machine Learning.
CoRR
Matthew Norton, Akiko Takeda, Alexander Mafusalov
2017 J jnl
Soft Margin Support Vector Classification as Buffered Probability Minimization.
J. Mach. Learn. Res.
Matthew Norton, Alexander Mafusalov, Stan Uryasev