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Journal Articles
- 2023
[j14]Jia Peter Liu
, Jiafeng Ye, Daniel Silva Izquierdo, Aleksandr Vinel, Nima Shamsaei, Shuai Shao:
A review of machine learning techniques for process and performance optimization in laser beam powder bed fusion additive manufacturing. J. Intell. Manuf. 34(8): 3249-3275 (2023)- [j13]Nasrin Mohabbati-Kalejahi, Alexander Vinel:
Risk parity: An alternative formulation for risk-averse stochastic optimization in presence of heavy-tailed distribution of losses. J. Oper. Res. Soc. 74(3): 797-810 (2023) - 2022
- [j12]Zuo Zeng, Alexander Vinel, Brianna Christian, Yasuhiro Shoji, Selen Cremaschi:
A graph theoretic approach to non-anticipativity constraint generation in multistage stochastic programs with incomplete scenario sets. Comput. Oper. Res. 146: 105886 (2022) - [j11]Ebrahim Mortaz, Alexander Vinel:
Predictive machine learning for prescriptive applications: A coupled training-validating approach. Knowl. Based Syst. 250: 109080 (2022) - [j10]Daniel F. Silva, Alexander Vinel, Bekircan Kirkici:
On-Demand Public Transit: A Markovian Continuous Approximation Model. Transp. Sci. 56(3): 704-724 (2022) - 2021
- [j9]Erhan Karakaya, Alexander Vinel, Alice E. Smith:
Relocations in container depots for different handling equipment types: Markov models. Comput. Ind. Eng. 157: 107311 (2021) - 2020
- [j8]Qiong Hu, Miao Cai, Nasrin Mohabbati-Kalejahi, Amir Mehdizadeh, Mohammad Ali Alamdar Yazdi, Alexander Vinel, Steven E. Rigdon, Karen C. Davis, Fadel M. Megahed:
A Review of Data Analytic Applications in Road Traffic Safety. Part 2: Prescriptive Modeling. Sensors 20(4): 1096 (2020) - [j7]Amir Mehdizadeh, Miao Cai, Qiong Hu, Mohammad Ali Alamdar Yazdi, Nasrin Mohabbati-Kalejahi, Alexander Vinel, Steven E. Rigdon, Karen C. Davis, Fadel M. Megahed:
A Review of Data Analytic Applications in Road Traffic Safety. Part 1: Descriptive and Predictive Modeling. Sensors 20(4): 1107 (2020) - 2017
- [j6]Alexander Vinel, Pavlo A. Krokhmal:
Certainty equivalent measures of risk. Ann. Oper. Res. 249(1-2): 75-95 (2017) - [j5]Alexander Vinel, Pavlo A. Krokhmal:
Mixed integer programming with a class of nonlinear convex constraints. Discret. Optim. 24: 66-86 (2017) - 2015
- [j4]Maciej Rysz, Alexander Vinel, Pavlo A. Krokhmal, Eduardo L. Pasiliao:
A Scenario Decomposition Algorithm for Stochastic Programming Problems with a Class of Downside Risk Measures. INFORMS J. Comput. 27(2): 416-430 (2015) - 2014
- [j3]Alexander Vinel, Pavlo A. Krokhmal:
On Valid Inequalities for Mixed Integer p-Order Cone Programming. J. Optim. Theory Appl. 160(2): 439-456 (2014) - [j2]Alexander Vinel, Pavlo A. Krokhmal:
Polyhedral approximations in p-order cone programming. Optim. Methods Softw. 29(6): 1210-1237 (2014) - 2013
- [j1]Yana Morenko, Alexander Vinel, Zhaohan Yu, Pavlo A. Krokhmal:
On p-norm linear discrimination. Eur. J. Oper. Res. 231(3): 784-789 (2013)
Conference and Workshop Papers
- 2020
- [c2]Joseph J. Kennedy, Armin Khayyer, Alexander Vinel, Alice E. Smith:
Efficient Risk Estimation Using Extreme Value Theory and Simulation Metamodeling. WSC 2020: 385-396 - 2018
- [c1]Alexander Vinel, Daniel F. Silva:
Probability Distribution of the Length of the Shortest Tour between a Few Random Points: a simulation Study. WSC 2018: 3156-3167
Informal and Other Publications
- 2021
- [i5]Xing Wang, Alexander Vinel:
Benchmarking Graph Neural Networks on Link Prediction. CoRR abs/2102.12557 (2021) - [i4]Ebrahim Mortaz, Alexander Vinel:
Predictive machine learning for prescriptive applications: a coupled training-validating approach. CoRR abs/2110.11826 (2021) - 2020
- [i3]Xing Wang, Alexander Vinel:
Cross Learning in Deep Q-Networks. CoRR abs/2009.13780 (2020) - [i2]Xing Wang, Alexander Vinel:
Reannealing of Decaying Exploration Based On Heuristic Measure in Deep Q-Network. CoRR abs/2009.14297 (2020) - [i1]Xing Wang, Yijun Wang, Bin Weng, Aleksandr Vinel:
Stock2Vec: A Hybrid Deep Learning Framework for Stock Market Prediction with Representation Learning and Temporal Convolutional Network. CoRR abs/2010.01197 (2020)
Coauthor Index
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