T. Trafalis

Theodore B. Trafalis, Huseyin Ince, T. Trafalis, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

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

Theodore Trafalis, Elaheh Jafarigol, T. Trafalis, 2020, SN Computer Science.

Robust Supply Chain Network Design by Considering Demand-Side Uncertainty and Supply-Side Disruption

Farrokh Mistree, Janet K. Allen, Theodore B. Trafalis, 2013, DAC 2013.

Rare events and imbalanced datasets: an overview

Maher Maalouf, Theodore B. Trafalis, T. Trafalis, 2011, Int. J. Data Min. Model. Manag..

Active Learning with Kernel Machines for Tornado Detection

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2008 .

Thyroid Nodule Benignty Prediction by Deep Feature Extraction

Yan Fang, Theodore Trafalis, Xiaomeng Dong, 2017, 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE).

Foreword

Theodore B. Trafalis, T. Trafalis, 2006, Computational Management Science.

Reinforcement Learning with Reduced States Using Kernels

Theodore B. Trafalis, Hicham Mansouri, T. Trafalis, 2006 .

Reinforcement Learning: An On-Line Framework Using Support Vectors

Hicham Mansouri, Theodore Trafalis, T. Trafalis, 2007, 2007 International Joint Conference on Neural Networks.

Guest Editorial

Marcello Sanguineti, Theodore B. Trafalis, O. Erhun Kundakcioglu, 2009, Comput. Manag. Sci..

Ocean Surface Wind Vector Forecasting Using Support Vector Regression

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2007 .

Real-Time Prediction Using Kernel Methods and Data Assimilation

S. Lakshmivarahan, Theodore B. Trafalis, Michael B. Richman, 2009 .

Machine Learning Techniques for Imbalanced Data: An Application for Tornado Detection

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2010 .

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

Theodore B. Trafalis, Ismail I. Almaraj, T. Trafalis, 2020, Computers & industrial engineering.

An integrated multi-echelon robust closed- loop supply chain under imperfect quality production

Theodore B. Trafalis, Ismail I. Almaraj, T. Trafalis, 2019 .

Learning Reliable Rules under Class Imbalance

Theodore B. Trafalis, Dimitrios I. Diochnos, T. Trafalis, 2021, SDM.

Machine-learning classifiers for imbalanced tornado data

S. Lakshmivarahan, Theodore B. Trafalis, Michael B. Richman, 2014, Comput. Manag. Sci..

Deterministic and Stochastic Logarithmic Barrier Function Methods for Neural Network Training

Theodore B. Trafalis, Tarek A. Tutunji, T. Trafalis, 1997 .

Primal-Dual Optimization Methods In Neural Networks And Support Vector Machines Training

Theodore B. Trafalis, T. Trafalis, 1999 .

Neural network training via an affine scaling quadratic optimization algorithm

Theodore B. Trafalis, Nicolas P. Couellan, Nicolas P. Couellan, 1996, Neural Networks.

Single-phase fluid flow classification via learning models

Theodore B. Trafalis, Olutayo O. Oladunni, T. Trafalis, 2011, Int. J. Gen. Syst..

Mixed-integer programming for kernel-based classifiers

Olutayo O. Oladunni, T. Trafalis, 2005 .

Two-phase flow regime identification with a multiclassification support vector machine (SVM) model

Theodore B. Trafalis, Olutayo O. Oladunni, Dimitrios V. Papavassiliou, 2005 .

Support vector machines and the electoral college

Theodore B. Trafalis, Alexander M. Malyscheff, T. Trafalis, 2003, Proceedings of ... International Joint Conference on Neural Networks.

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

Theodore B. Trafalis, Michael B. Richman, Olutayo O. Oladunni, 2011, Comput. Manag. Sci..

Support Vector Machines Applied to Multivariate Processes

Theodore B. Trafalis, Robin C. Gilbert, T. Trafalis, 2010 .

Neural Networks Approaches for Combinatorial Optimization Problems

Theodore B. Trafalis, Suat Kasap, T. Trafalis, 1999, Handbook of Combinatorial Optimization.

Machine Learning Classifiers for Tornado Detection: Sensitivity Analysis on Tornado Data Sets

S. Lakshmivarahan, Theodore B. Trafalis, Michael B. Richman, 2006 .

Active Learning with Support Vector Machines for Tornado Prediction

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2007, International Conference on Computational Science.

A Pipeline Support Vector Regression Method to Thin Large Ocean Surface Wind Data On-Line

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2008 .

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

Theodore B. Trafalis, Olutayo O. Oladunni, Dimitrios V. Papavassiliou, 2006, International Conference on Computational Science.

Single Phase Laminar & Turbulent Flow Classification via a Knowledge-Based Linear Model

Olutayo O. Oladunni, T. Trafalis, 2006 .

Kernel methods for short-term portfolio management

Theodore B. Trafalis, Huseyin Ince, T. Trafalis, 2006, Expert Syst. Appl..

Support Vector Machines for Classification

Theodore B. Trafalis, Indra Adrianto, Robin C. Gilbert, 2011 .

Unsupervised Neural Network Training Via a Potential Reduction Approach

Theodore B. Trafalis, Cornelis Roos, Joost P. Warners, 1996 .

An approximation to max min fairness in multi commodity networks

Theodore B. Trafalis, Hamoud S. Bin Obaid, T. Trafalis, 2018, Comput. Manag. Sci..

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

Wei Sun, T. Trafalis, 2023, 2023 American Control Conference (ACC).

Learning-Based Nonlinear $H^\infty$ Control via Game-Theoretic Differential Dynamic Programming

Theodore B. Trafalis, Wei Sun, Wei Sun, 2021, 2107.04507.

A differential dynamic programming algorithm for differential games

T. Morin, T. Trafalis, 2001 .

MULTIPLE IMPUTATION THROUGH MACHINE LEARNING ALGORITHMS

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2006 .

Constructing an Efficient Machine Learning Model for Tornado Prediction

T. Trafalis, F. Aleskerov, V. Yakuba, 2018, Int. J. Inf. Technol. Decis. Mak..

Risk-Based Maintenance of a Cross-Country Petroleum Pipeline System

Alex W. Dawotola, T. B. Trafalis, Zahiraniza Mustaffa, 2013 .

Support Vector Regression for Determination of Minimum Zone

Theodore B. Trafalis, Shivakumar Raman, Chakguy Prakasvudhisarn, 2003 .

Fairness in Resource Allocation: Foundation and Applications

Theodore B. Trafalis, Hamoud S. Bin-Obaid, T. Trafalis, 2018 .

Data mining techniques for improved WSR-88D rainfall estimation

Theodore B. Trafalis, Michael B. Richman, Budi Santosa, 2002 .

Rule-Based Support Vector Machine Classifiers Applied to Tornado Prediction

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2004, International Conference on Computational Science.

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

Theodore B. Trafalis, Kash Barker, Cameron A. MacKenzie, 2014, Stat. Anal. Data Min..

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

Theodore B. Trafalis, Samir A. Alwazzi, T. Trafalis, 2010, Int. J. Gen. Syst..

Support vector regression to predict asphalt mix performance

Maher Maalouf, Theodore B. Trafalis, Naji Khoury, 2008 .

2-Facility manifold location routing problem

T. Trafalis, Emre Tokgöz, 2015, Optimization Letters.

Kernel classification using a linear programming approach

Theodore B. Trafalis, Alexander M. Malyscheff, T. Trafalis, 2019, Annals of Mathematics and Artificial Intelligence.

Natural gas storage valuation via least squares Monte Carlo and support vector regression

Theodore B. Trafalis, Alexander M. Malyscheff, T. Trafalis, 2017 .

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

Theodore B. Trafalis, Olutayo O. Oladunni, T. Trafalis, 2009, Eur. J. Oper. Res..

Real-time prediction of order flowtimes using support vector regression

Theodore B. Trafalis, Scott A. Moses, Abdulrahman Alenezi, 2008, Comput. Oper. Res..

Mathematical Foundations for Form Inspection and Adaptive

Theodore B. Trafalis, Juan Antonio Aguirre-Cruz, Shivakumar Raman, 2011 .

Learning from student data

T.R. Rhoads, K. Barker, T. Trafalis, 2004, Proceedings of the 2004 IEEE Systems and Information Engineering Design Symposium, 2004..

Tornado Detection with Support Vector Machines

Theodore B. Trafalis, Michael B. Richman, Huseyin Ince, 2003, International Conference on Computational Science.

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

T. Trafalis, Peyman Hekmatpour, W. Keely, 2023, Society.

Tornado Detection with Support Vector Machines

T. Trafalis, M. B. Richman, Huseyin Ince, 2003, International Conference on Computational Science.

An interactive analytic center trade-off cutting plane algorithm for multiobjective linear programming

Theodore B. Trafalis, T. Trafalis, Rashid M. Alkahtani, 1999 .

Robust Data Mining

P. Pardalos, T. Trafalis, P. Xanthopoulos, 2012 .

Neural Networks for Combinatorial Optimization

Emile H. L. Aarts, H. P. Stehouwer, J Jaap Wessels, 2009, Encyclopedia of Optimization.

Learning Networks For Tornado Forecasting:A Bayesian Perspective

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2005 .

A nonlinear multi-classification knowledge-based kernel machine

Theodore B. Trafalis, Olutayo O. Oladunni, T. Trafalis, 2009, Comput. Manag. Sci..

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

Theodore B. Trafalis, Olutayo O. Oladunni, T. Trafalis, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.