Theodore B. Trafalis

According to our database, Theodore B. Trafalis authored at least 68 papers between 1990 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A distributed approach to meteorological predictions: addressing data imbalance in precipitation prediction models through federated learning and GANs.

Elaheh Jafarigol, Theodore B. Trafalis

Comput. Manag. Sci., June, 2024

2023

Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations.

Elaheh Jafarigol, Theodore B. Trafalis, Talayeh Razzaghi, Mona Zamankhani

CoRR, 2023

The Paradox of Noise: An Empirical Study of Noise-Infusion Mechanisms to Improve Generalization, Stability, and Privacy in Federated Learning.

Elaheh Jafarigol, Theodore B. Trafalis

CoRR, 2023

Religious Affiliation in the Twenty-First Century: A Machine Learning Perspective on the World Value Survey.

Elaheh Jafarigol, William Keely, Tess Hartog, Tom Welborn, Peyman Hekmatpour, Theodore B. Trafalis

CoRR, 2023

A Review of Machine Learning Techniques in Imbalanced Data and Future Trends.

Elaheh Jafarigol, Theodore B. Trafalis

CoRR, 2023

Learning-Based Nonlinear H^∞ Control via Game-Theoretic Differential Dynamic Programming.

Wei Sun, Theodore B. Trafalis

Proceedings of the American Control Conference, 2023

2022

A robust global optimisation framework for stochastic integrated refinery planning with demand and price uncertainties.

Mahmud R. Siamizade, Theodore B. Trafalis

Int. J. Math. Oper. Res., 2022

A robust optimization approach in a multi-objective closed-loop supply chain model under imperfect quality production.

Ismail I. Almaraj, Theodore B. Trafalis

Ann. Oper. Res., 2022

Autonomous Learning Rate Optimization for Deep Learning.

Xiaomeng Dong, Tao Tan, Michael Potter, Yun-Chan Tsai, Gaurav Kumar, V. Ratna Saripalli, Theodore B. Trafalis

Proceedings of the Learning and Intelligent Optimization - 16th International Conference, 2022

Optimizing Data Augmentation Policy Through Random Unidimensional Search.

Xiaomeng Dong, Michael Potter, Gaurav Kumar, Yun-Chan Tsai, V. Ratna Saripalli, Theodore B. Trafalis

Proceedings of the Learning and Intelligent Optimization - 16th International Conference, 2022

2021

Learning Reliable Rules under Class Imbalance.

Dimitrios I. Diochnos, Theodore B. Trafalis

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

2020

Deep MLP-CNN Model Using Mixed-Data to Distinguish between COVID-19 and Non-COVID-19 Patients.

Md. Manjurul Ahsan, Tasfiq E. Alam, Theodore B. Trafalis, Pedro Huebner

Symmetry, 2020

Imbalanced Learning with Parametric Linear Programming Support Vector Machine for Weather Data Application.

Elaheh Jafarigol, Theodore B. Trafalis

SN Comput. Sci., 2020

Constructing an Efficient Machine Learning Model for Tornado Prediction.

Fuad Aleskerov, Sergey Demin, Michael B. Richman, Sergey Shvydun, Theodore B. Trafalis, Vyacheslav Yakuba

Int. J. Inf. Technol. Decis. Mak., 2020

An approximation to max min fairness in multi commodity networks.

Hamoud S. Bin Obaid, Theodore B. Trafalis

Comput. Manag. Sci., 2020

Affinely adjustable robust optimization under dynamic uncertainty set for a novel robust closed-loop supply chain.

Ismail I. Almaraj, Theodore B. Trafalis

Comput. Ind. Eng., 2020

Kernel classification using a linear programming approach.

Alexander M. Malyscheff, Theodore B. Trafalis

Ann. Math. Artif. Intell., 2020

2018

Logistic regression in large rare events and imbalanced data: A performance comparison of prior correction and weighting methods.

Maher Maalouf, Dirar Homouz, Theodore B. Trafalis

Comput. Intell., 2018

2017

A data-driven kernel method assimilation technique for geophysical modelling.

Robin C. Gilbert, Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie

Optim. Methods Softw., 2017

2-Facility manifold location routing problem.

Emre Tokgöz, Theodore B. Trafalis

Optim. Lett., 2017

Thyroid Nodule Benignty Prediction by Deep Feature Extraction.

XueYan Mei, Xiaomeng Dong, Timothy Deyer, Jingyi Zeng, Theodore B. Trafalis, Yan Fang

Proceedings of the 17th IEEE International Conference on Bioinformatics and Bioengineering, 2017

2015

A heuristic algorithm to solve the single-facility location routing problem on Riemannian surfaces.

Emre Tokgöz, Samir A. Alwazzi, Theodore B. Trafalis

Comput. Manag. Sci., 2015

A Single-Facility Manifold Location Routing Problem with an Application to Supply Chain Management and Robotics.

Emre Tokgöz, Iddrisu Awudu, Theodore B. Trafalis

Proceedings of the Machine Learning, Optimization, and Big Data, 2015

2014

A Bayesian beta kernel model for binary classification and online learning problems.

Cameron A. MacKenzie, Theodore B. Trafalis, Kash Barker

Stat. Anal. Data Min., 2014

Machine-learning classifiers for imbalanced tornado data.

Theodore B. Trafalis, Indra Adrianto, Michael B. Richman, S. Lakshmivarahan

Comput. Manag. Sci., 2014

Preface: Special volume on data mining and informatics.

Victoria C. P. Chen, Seoung Bum Kim, Theodore B. Trafalis

Ann. Oper. Res., 2014

2013

On-line SVM learning via an incremental primal-dual technique.

Nicolas P. Couellan, Theodore B. Trafalis

Optim. Methods Softw., 2013

An incremental primal-dual method for nonlinear programming with special structure.

Nicolas P. Couellan, Theodore B. Trafalis

Optim. Lett., 2013

Time-series Analysis for Detecting Structure Changes and Suspicious Accounting Activities in Public Software Companies.

Zhen Zhang, Theodore B. Trafalis

Proceedings of the Complex Adaptive Systems 2013 Conference, 2013

2011

Single-phase fluid flow classification via learning models.

Olutayo O. Oladunni, Theodore B. Trafalis

Int. J. Gen. Syst., 2011

Rare events and imbalanced datasets: an overview.

Maher Maalouf, Theodore B. Trafalis

Int. J. Data Min. Model. Manag., 2011

Robust weighted kernel logistic regression in imbalanced and rare events data.

Maher Maalouf, Theodore B. Trafalis

Comput. Stat. Data Anal., 2011

Linear classification tikhonov regularization knowledge-based support vector machine for tornado forecasting.

Theodore B. Trafalis, Olutayo O. Oladunni, Michael B. Richman

Comput. Manag. Sci., 2011

Kernel logistic regression using truncated Newton method.

Maher Maalouf, Theodore B. Trafalis, Indra Adrianto

Comput. Manag. Sci., 2011

2010

The p-Centre machine for regression analysis.

Indra Adrianto, Theodore B. Trafalis

Optim. Methods Softw., 2010

Support vector machine classification with noisy data: a second order cone programming approach.

Theodore B. Trafalis, Samir A. Alwazzi

Int. J. Gen. Syst., 2010

2009

Neural Networks for Combinatorial Optimization.

Theodore B. Trafalis, Suat Kasap

Proceedings of the Encyclopedia of Optimization, Second Edition, 2009

Quadratic programming formulations for classificationand regression.

Robin C. Gilbert, Theodore B. Trafalis

Optim. Methods Softw., 2009

Support vector machines for spatiotemporal tornado prediction.

Indra Adrianto, Theodore B. Trafalis, Valliappa Lakshmanan

Int. J. Gen. Syst., 2009

A regularized pairwise multi-classification knowledge-based machine and applications.

Olutayo O. Oladunni, Theodore B. Trafalis

Eur. J. Oper. Res., 2009

A nonlinear multi-classification knowledge-based kernel machine.

Olutayo O. Oladunni, Theodore B. Trafalis

Comput. Manag. Sci., 2009

Guest Editorial.

O. Erhun Kundakcioglu, Marcello Sanguineti, Theodore B. Trafalis

Comput. Manag. Sci., 2009

2008

Short term forecasting with support vector machines and application to stock price prediction.

Huseyin Ince, Theodore B. Trafalis

Int. J. Gen. Syst., 2008

Real-time prediction of order flowtimes using support vector regression.

Abdulrahman Alenezi, Scott A. Moses, Theodore B. Trafalis

Comput. Oper. Res., 2008

2007

Robust support vector machines for classification and computational issues.

Theodore B. Trafalis, Robin C. Gilbert

Optim. Methods Softw., 2007

Support vector regression with noisy data: a second order cone programming approach.

Theodore B. Trafalis, Samir A. Alwazzi

Int. J. Gen. Syst., 2007

Robust multiclass kernel-based classifiers.

Budi Santosa, Theodore B. Trafalis

Comput. Optim. Appl., 2007

Regularization Based Classification Models.

Olutayo O. Oladunni, Theodore B. Trafalis

Proceedings of the International Joint Conference on Neural Networks, 2007

Active Learning with Support Vector Machines for Tornado Prediction.

Theodore B. Trafalis, Indra Adrianto, Michael B. Richman

Proceedings of the Computational Science, 2007

Regularized Knowledge-Based Kernel Machine.

Olutayo O. Oladunni, Theodore B. Trafalis

Proceedings of the Computational Science, 2007

2006

Learning networks for tornado detection.

Theodore B. Trafalis, Budi Santosa, Michael B. Richman

Int. J. Gen. Syst., 2006

Kernel methods for short-term portfolio management.

Huseyin Ince, Theodore B. Trafalis

Expert Syst. Appl., 2006

Robust classification and regression using support vector machines.

Theodore B. Trafalis, Robin C. Gilbert

Eur. J. Oper. Res., 2006

A hybrid model for exchange rate prediction.

Huseyin Ince, Theodore B. Trafalis

Decis. Support Syst., 2006

Foreword.

Theodore B. Trafalis

Comput. Manag. Sci., 2006

A Pairwise Reduced Kernel-based Multi-classification Tikhonov Regularization Machine.

Olutayo O. Oladunni, Theodore B. Trafalis

Proceedings of the International Joint Conference on Neural Networks, 2006

Detection of Tornados Using an Incremental Revised Support Vector Machine with Filters.

Hyung-Jin Son, Theodore B. Trafalis

Proceedings of the Computational Science, 2006

Knowledge-Based Multiclass Support Vector Machines Applied to Vertical Two-Phase Flow.

Olutayo O. Oladunni, Theodore B. Trafalis, Dimitrios V. Papavassiliou

Proceedings of the Computational Science, 2006

2005

Learning networks in rainfall estimation.

Theodore B. Trafalis, Budi Santosa, Michael B. Richman

Comput. Manag. Sci., 2005

2004

Rule-Based Support Vector Machine Classifiers Applied to Tornado Prediction.

Theodore B. Trafalis, Budi Santosa, Michael B. Richman

Proceedings of the Computational Science, 2004

2003

Tornado Detection with Support Vector Machines.

Theodore B. Trafalis, Huseyin Ince, Michael B. Richman

Proceedings of the Computational Science - ICCS 2003, 2003

2002

An Analytic Center Machine.

Theodore B. Trafalis, Alexander M. Malyscheff

Mach. Learn., 2002

A novel metaheuristics approach for continuous global optimization.

Theodore B. Trafalis, Suat Kasap

J. Glob. Optim., 2002

2000

Support Vector Machine for Regression and Applications to Financial Forecasting.

Theodore B. Trafalis, Huseyin Ince

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999

Neural Networks Approaches for Combinatorial Optimization Problems.

Theodore B. Trafalis, Suat Kasap

Proceedings of the Handbook of Combinatorial Optimization, 1999

1997

Training of supervised neural networks via a nonlinear primal-dual interior-point method.

Theodore B. Trafalis, Nicolas P. Couellan, Sébastien C. Bertrand

Proceedings of International Conference on Neural Networks (ICNN'97), 1997

1996

Neural network training via an affine scaling quadratic optimization algorithm.

Theodore B. Trafalis, Nicolas P. Couellan

Neural Networks, 1996

1990

Centers and Invariant Points of Convex Bodies.

Mark J. Kaiser, Thomas L. Morin, Theodore B. Trafalis

Proceedings of the Applied Geometry And Discrete Mathematics, 1990