Theodore B. Trafalis

发表

Computational Statistics and Data Analysis Robust Weighted Kernel Logistic Regression in Imbalanced and Rare Events Data

Maher Maalouf, Theodore B. Trafalis, T. Trafalis, 2022 .

The p-Centre machine for regression analysis

Theodore B. Trafalis, Indra Adrianto, T. Trafalis, 2010, Optim. Methods Softw..

Support vector machine classification of uncertain and imbalanced data using robust optimization

Theodore B. Trafalis, Raghav Pant, Kash Barker, 2011 .

Uncertainty and sensitivity analysis in support vector machines: robust optimization and uncertain programming approaches

Theodore B. Trafalis, Jin Park, 2006 .

Examining Churn and Loyalty Using Support Vector Machine

Theodore B. Trafalis, Ali Dehghan, T. Trafalis, 2012 .

Architecture selection for neural networks

Theodore B. Trafalis, P. Karampiperis, N. Manouselis, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Support Vector Machines for Classification

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

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

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

Single-phase fluid flow classification via learning models

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

Missing Data Imputation Through Machine Learning Algorithms

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2009 .

An Incremental Nonlinear Primal-Dual Algorithm and Applications to Artificial Neural Networks Training

Theodore B. Trafalis, Nicolas Couellan, 1998 .

Tornado Detection with Support Vector Machines

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

Constructing an Efficient Machine Learning Model for Tornado Prediction

Fuad Aleskerov, Theodore B. Trafalis, Michael B. Richman, 2020, Int. J. Inf. Technol. Decis. Mak..

An approximation to max min fairness in multi commodity networks

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

Uncertainty and sensitivity analysis issues in support vector machines

Theodore B. Trafalis, Jin Park, 2006 .

Rare events and imbalanced datasets: an overview

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

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

Zhen Zhang, Theodore B. Trafalis, 2013, Complex Adaptive Systems.

Data selection using support vector regression

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2015, Advances in Atmospheric Sciences.

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

Theodore B. Trafalis, T. Trafalis, 1999 .

Feature selection of radar-derived attributes with linear programming support vector machines

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

A nonlinear multi-classification knowledge-based kernel machine

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

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.

Machine Learning Methods for Data Assimilation

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2010 .

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

Maher Maalouf, Theodore B. Trafalis, Dirar Homouz, 2018, Comput. Intell..

Support vector machine for regression and applications to financial forecasting

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.

Rule-Based Support Vector Machine Classifiers Applied to Tornado Prediction

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

Real-time prediction of order flowtimes using support vector regression

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

Neural Network Training via Quadratic Programming

Theodore B. Trafalis, Nicolas Couellan, 1997 .

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.

Kernel logistic regression using truncated Newton method

Maher Maalouf, Theodore B. Trafalis, Indra Adrianto, 2011, Comput. Manag. Sci..

Kernel methods for short-term portfolio management

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

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

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

Foreword

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

Support Vector Machines and Applications

Theodore B. Trafalis, Olutayo O. Oladunni, 2008 .

Manifold Location Routing Problem with Applications in Network Theory

Theodore B. Trafalis, Emre Tokgoz, 2014 .

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..

Machine-learning classifiers for imbalanced tornado data

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

Guest Editorial

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

Determination oftheOptimal BatchSizeinIncremental Approaches: AnApplication toTornado Detection

Theodore B. Trafalis, Michael B. Richman, Hyung-Jin Son, 2005 .

A Hybrid Forecasting Model for Stock Market Prediction

Theodore B. Trafalis, Huseyin Ince, 2017 .

Quadratic programming formulations for classificationand regression

Theodore B. Trafalis, Robin C. Gilbert, 2009, Optim. Methods Softw..

An Analytic Center Machine

Theodore B. Trafalis, Alexander M. Malyscheff, T. Trafalis, 2002, Machine Learning.

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

Theodore B. Trafalis, Huseyin Ince, T. Trafalis, 2008, Int. J. Gen. Syst..

Adaptive methods in coordinate metrology

Theodore B. Trafalis, Shivakumar Raman, Robin C. Gilbert, 2005, SPIE Optics East.

Neural Networks for Combinatorial Optimization

Theodore B. Trafalis, Suat Kasap, 2009, Encyclopedia of Optimization.

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 .

Active Learning with Kernel Machines for Tornado Detection

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

Unsupervised Neural Network Training Via a Potential Reduction Approach

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

Learning networks for tornado detection

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2006, Int. J. Gen. Syst..

Real-Time Prediction Using Kernel Methods and Data Assimilation

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

Learning networks in rainfall estimation

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2005, Comput. Manag. Sci..

Support vector machines for spatiotemporal tornado prediction

Theodore B. Trafalis, Indra Adrianto, Valliappa Lakshmanan, 2009, Int. J. Gen. Syst..

Robust classification and regression using support vector machines

Theodore B. Trafalis, Robin C. Gilbert, T. Trafalis, 2006, Eur. J. Oper. Res..

Support Vector Machines Applied to Multivariate Processes

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

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

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

Coordinate metrology for adaptive form verification

Theodore B. Trafalis, Shivakumar Raman, Robin C. Gilbert, 2013 .

Linear Max-Min Fairness in Multi-commodity Flow Networks

Theodore B. Trafalis, Hamoud S. Bin Obaid, 2016 .

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

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

Linear Discriminant Analysis

Panos M. Pardalos, Theodore B. Trafalis, Petros Xanthopoulos, 2013 .

Robust support vector machines for classification and computational issues

Theodore B. Trafalis, Robin C. Gilbert, T. Trafalis, 2007, Optim. Methods Softw..

2-Facility manifold location routing problem

Theodore B. Trafalis, Emre Tokgoz, 2017, Optim. Lett..

An incremental primal–dual method for nonlinear programming with special structure

Theodore B. Trafalis, Nicolas P. Couellan, Nicolas P. Couellan, 2011, Optimization Letters.

Support vector regression to predict asphalt mix performance

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

Support vector machines and the electoral college

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

A data-driven kernel method assimilation technique for geophysical modelling

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2017, Optim. Methods Softw..

A Hybrid Scatter Genetic Tabu Approach for Continuous Global Optimization

Theodore B. Trafalis, Ibrahim M. Al-Harkan, Ibrahim M. Al-Harkan, 2002 .

Neural network training via an affine scaling quadratic optimization algorithm

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

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

Theodore B. Trafalis, Samir A. Alwazzi, T. Trafalis, 2007, Int. J. Gen. Syst..

Principal Component Analysis

Panos M. Pardalos, Theodore B. Trafalis, Petros Xanthopoulos, 2013 .

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

Theodore B. Trafalis, Nicolas Couellan, S. C. Bertrand, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

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

Theodore B. Trafalis, Hyung-Jin Son, 2006, International Conference on Computational Science.

Neural Networks Approaches for Combinatorial Optimization Problems

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

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

Theodore B. Trafalis, Emre Tokgoz, Samir A. Alwazzi, 2015, Comput. Manag. Sci..

Malware Detection for Forensic Memory Using Deep Recurrent Neural Networks

Theodore B. Trafalis, Ioannis Karamitsos, Aishwarya Afzulpurkar, 2020 .

Robust Data Mining

Panos M. Pardalos, Petros Xanthopoulos, Theodore B. Trafalis, 2012 .

Kernel classification using a linear programming approach

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

Preface: Special volume on data mining and informatics

Seoung Bum Kim, Theodore B. Trafalis, Victoria C. P. Chen, 2014, Ann. Oper. Res..

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

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

Regularization Based Classification Models

Theodore B. Trafalis, Olutayo O. Oladunni, 2007, 2007 International Joint Conference on Neural Networks.

Plenary lecture 3: new developments of kernel methods in weather prediction and applications

Theodore B. Trafalis, 2011 .

Learning Networks For Tornado Forecasting:A Bayesian Perspective

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

A novel metaheuristics approach for continuous global optimization

Theodore B. Trafalis, Suat Kasap, T. Trafalis, 2002, J. Glob. Optim..

Active Learning with Support Vector Machines for Tornado Prediction

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

Reinforcement Learning with Reduced States Using Kernels

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

Deterministic and Stochastic Logarithmic Barrier Function Methods for Neural Network Training

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

Fairness in Resource Allocation: Foundation and Applications

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

Support Vector Machines

Panos M. Pardalos, Theodore B. Trafalis, Petros Xanthopoulos, 2013 .

A hybrid model for exchange rate prediction

Theodore B. Trafalis, Huseyin Ince, T. Trafalis, 2006, Decis. Support Syst..

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.

A Hybrid Knowledge Based-Clustering Multi-Class SVM Approach for Genes Expression Analysis

Tyrrell Conway, Budi Santosa, Theodore B. Trafalis, 2007 .

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..

Data Mining Techniques for Pattern Recognition: Tornado Signatures in Doppler Weather Radar Data

Theodore B. Trafalis, Anderson White, 2003 .

Incremental kernel learning algorithms and applications

Theodore B. Trafalis, Hyung-Jin Son, 2006 .

Regularized Knowledge-Based Kernel Machine

Theodore B. Trafalis, Olutayo O. Oladunni, T. Trafalis, 2007, 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..

Robust multiclass kernel-based classifiers

Budi Santosa, Theodore B. Trafalis, 2007, Comput. Optim. Appl..

Tornado Detection with Kernel-Based Classifiers from WSR-88D Radar Data

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2016 .

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

Theodore B. Trafalis, Nicolas P. Couellan, 2013, Optim. Methods Softw..

Prediction of Rainfall from WSR-88D Radar Using Kernel-Based Methods

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2003 .

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

Theodore B. Trafalis, Emre Tokgoz, Iddrisu Awudu, 2015, MOD.

SVM Classification of Uncertain Data Using Robust Multi-Kernel Methods

Theodore B. Trafalis, Raghav Pant, 2015 .

Mathematical Foundations for Form Inspection and Adaptive

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

Learning Reliable Rules under Class Imbalance

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

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

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

MULTIPLE IMPUTATION THROUGH MACHINE LEARNING ALGORITHMS

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

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

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

Benders decomposition technique for support vector regression

Theodore B. Trafalis, Huseyin Ince, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Data mining techniques for improved WSR-88D rainfall estimation

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

Least square multi-classification support vector machines: pair-wise (P A LS-MSVM) & piece-wise (P I LS-MSVM) formulations

Theodore B. Trafalis, Olutayo O. Oladunni, T. Trafalis, 2005 .

Support Vector Regression for Determination of Minimum Zone

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

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.

Ocean Surface Wind Vector Forecasting Using Support Vector Regression

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

Variable selection and prediction of rainfall from WSR-88D radar using support vector regression

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

Kernel principal component analysis and support vector machines for stock price prediction

Theodore B. Trafalis, Huseyin Ince, T. Trafalis, 2007 .

An interior point multiobjective programming approach for production planning with uncertain information

Theodore B. Trafalis, Bobbie L. Foote, Tsutomu Mishina, 1999 .

A Circumscribed Ellipsoid Method for Multiobjective Programming and Applications to Financial Planning

Theodore B. Trafalis, Tsutomu Mishina, T. Trafalis, 1997 .

Interior Point Methods for Supervised Training of Artificial Neural Networks with Bounded Weights

Nicolas Couellan, Theodore B. Trafalis, Tarek A. Tutunji, 1997 .

Form inspection using kernel methods

Theodore B. Trafalis, Shivakumar Raman, Robin C. Gilbert, 2010 .

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

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

Least Squares Problems

Panos M. Pardalos, Petros Xanthopoulos, Theodore B. Trafalis, 2013 .

Mixed-Integer Multiobjective Process Planning under Uncertainty

Miguel J. Bagajewicz, Theodore B. Trafalis, Hernán Rodera, 2002 .