Mark J. Embrechts - researchr alias

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Viewing Publication 1 - 52 from 52

2014

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013)Mark J. Embrechts, Fabrice Rossi, Frank-Michael Schleif, John A. Lee. ijon, 141:1-2, 2014. [doi]

An application of the temporal difference algorithm to the truck backer-upper problemChristopher J. Gatti, Mark J. Embrechts. esann 2014: [doi]

2013

Using sensitivity analysis and visualization techniques to open black box data mining modelsPaulo Cortez, Mark J. Embrechts. isci, 225:1-17, 2013. [doi]

Random Brains: An ensemble method for feature selection with neural networksMark J. Embrechts, Jonathan D. Linton, Jorge M. Santos. esann 2013: [doi]

An empirical analysis of reinforcement learning using design of experimentsChristopher J. Gatti, Mark J. Embrechts, Jonathan D. Linton. esann 2013: [doi]

Erratum to "Taguchi-fuzzy multi output optimization (MOO) in high speed CNC turning of AISI P-20 tool steel" [Exp. Syst. Appl. 38(6) (2011) 6822-6828]Jonathan D. Linton, Quanhong Jiang, Christopher J. Gatti, Mark J. Embrechts. eswa, 40(4):1408-1409, 2013. [doi]

Erratum to "Multi-attribute decision making for green electrical discharge machining" [Expert Syst. Appl. 38(7) (2011) 8370-8374]Jonathan D. Linton, Quanhong Jiang, Christopher J. Gatti, Mark J. Embrechts. eswa, 40(4):1407, 2013. [doi]

Discussion of Kapsiz, M., Durat, M., Ficici, F. (2011). Friction and wear studies between cylinder liner and piston ring pair using Taguchi design method. Advances in Engineering Software, 42(8), 595-603Jonathan D. Linton, Quanhong Jiang, Christopher J. Gatti, Mark J. Embrechts. aes, 64:71-73, 2013. [doi]

2012

Hybrid hierarchical clustering: cluster assessment via cluster validation indicesMark J. Embrechts, Jonathan D. Linton, Christopher J. Gatti. esann 2012: [doi]

Forecasting exchange rates with ensemble neural networks and ensemble K-PLS: A case study for the US Dollar per Indian RupeeMark J. Embrechts, Christopher J. Gatti, Jonathan D. Linton, Thiemo Gruber, Bernhard Sick. ijcnn 2012: 1-8 [doi]

2011

Opening black box Data Mining models using Sensitivity AnalysisPaulo Cortez, Mark J. Embrechts. cidm 2011: 341-348 [doi]

A brief tutorial on reinforcement learning: The game of Chung ToiChristopher J. Gatti, Jonathan D. Linton, Mark J. Embrechts. esann 2011: [doi]

Reinforcement learning and the effects of parameter settings in the game of Chung ToiChristopher J. Gatti, Mark J. Embrechts, Jonathan D. Linton. SMC 2011: 3530-3535 [doi]

2010

An augmented efficient backpropagation training strategy for deep autoassociative neural networksMark J. Embrechts, Blake J. Hargis, Jonathan D. Linton. esann 2010: [doi]

Augmented Efficient BackProp for backpropagation learning in deep autoassociative neural networksMark J. Embrechts, Blake J. Hargis, Jonathan D. Linton. ijcnn 2010: 1-6 [doi]

2009

Reservoir Size, Spectral Radius and Connectivity in Static Classification ProblemsLuÃs A. Alexandre, Mark J. Embrechts. icann 2009: 1015-1024 [doi]

Benchmarking reservoir computing on time-independent classification tasksLuís A. Alexandre, Mark J. Embrechts, Jamathan Linton. ijcnn 2009: 89-93 [doi]

Reservoir computing for static pattern recognitionMark J. Embrechts, Luís A. Alexandre, Jonathan D. Linton. esann 2009: [doi]

2008

Analyzing currency crises real effects with partial least squares sensitivity analysisIsmael E. Arciniegas Rueda, Fabio A. Arciniegas, Mark J. Embrechts. ida, 12(1):103-128, 2008. [doi]

Identification of ischemic heart disease via machine learning analysis on magnetocardiogramsTanawut Tantimongcolwat, Thanakorn Naenna, Chartchalerm Isarankura-Na-Ayudhya, Mark J. Embrechts, Virapong Prachayasittikul. cbm, 38(7):817-825, 2008. [doi]

2007

2006

Efficient chromosome encoding and problem-specific mutation methods for the flexible bay facility layout problemNeil H. W. Eklund, Mark J. Embrechts, Marc Goetschalckx. tsmc, 36(4):495-502, 2006. [doi]

Feature Selection via Sensitivity Analysis with Direct Kernel PLSMark J. Embrechts, Robert A. Bress, Robert H. Kewley. In Isabelle Guyon, Masoud Nikravesh, Steve R. Gunn, Lotfi A. Zadeh, editors, Feature Extraction - Foundations and Applications. Volume 207 of Studies in Fuzziness and Soft Computing, pages 447-462, Springer, 2006. [doi]

Data Fusion for Outlier Detection through Pseudo-ROC Curves and Rank DistributionsPaul F. Evangelista, Mark J. Embrechts, Boleslaw K. Szymanski. ijcnn 2006: 2166-2173 [doi]

Kernel Partial Least Squares for the Identification of Mixture Content from TeraHertz SpectraLong Han, Mark J. Embrechts, Yunqing Chen, Xi-Cheng Zhang. ijcnn 2006: 3181-3187 [doi]

Random Forests Feature Selection with K-PLS: Detecting Ischemia from MagnetocardiogramsLong Han, Mark J. Embrechts, Boleslaw K. Szymanski, Karsten Sternickel, Alexander Ross. esann 2006: 221-226 [doi]

2005

2004

Predicting Protein-Ligand Binding Affinities Using Novel Geometrical Descriptors and Machine-Learning MethodsWei Deng, Curt M. Breneman, Mark J. Embrechts. jcisd, 44(2):699-703, 2004. [doi]

Hybrid identification of nuclear power plant transients with artificial neural networksMark J. Embrechts, Sándor Benedek. tie, 51(3):686-693, 2004. [doi]

Introduction to Scientific Data Mining: Direct Kernel Methods and ApplicationsMark J. Embrechts, Boleslaw K. Szymanski, Karsten Sternickel. In Seppo J. Ovaska, editor, Computationally Intelligent Hybrid Systems. pages 317-362, Wiley, 2004. [doi]

Taming the Curse of Dimensionality in Kernels and Novelty DetectionPaul F. Evangelista, Mark J. Embrechts, Boleslaw K. Szymanski. softco 2004: 425-438 [doi]

Applying Support Vector Machines to Breast Cancer Diagnosis using Screen Film Mammogram DataWalker H. Land Jr., Lut Wong, Dan McKee, Mark J. Embrechts, Rizly Salih, Frances Anderson. cbms 2004: 224 [doi]

SVM sensitivity analysis: an application to currency crises aftermathsIsmael E. Arciniegas Rueda, Fabio A. Arciniegas, Mark J. Embrechts. tsmc, 34(3):387-398, 2004. [doi]

Detection and Classification of Organophosphate Nerve Agent Simulants Using Support Vector Machines with Multiarray SensorsOmowunmi Sadik, Walker H. Land Jr., Adam K. Wanekaya, Michiko Uematsu, Mark J. Embrechts, Lut Wong, Dale Leibensperger, Alex Volykin. jcisd, 44(2):499-507, 2004. [doi]

2003

Dimensionality Reduction via Sparse Support Vector MachinesJinbo Bi, Kristin P. Bennett, Mark J. Embrechts, Curt M. Breneman, Minghu Song. jmlr, 3:1229-1243, 2003. [doi]

New developments in PEST shape/property hybrid descriptorsCurt M. Breneman, C. Matthew Sundling, Nagamani Sukumar, Lingling Shen, William P. Katt, Mark J. Embrechts. jcamd, 17(2-4):231-240, 2003.

Use of machine learning for classification of magnetocardiogramsMark J. Embrechts, Boleslaw K. Szymanski, Karsten Sternickel, Thanakorn Naenna, Ramathilagam Bragaspathi. SMC 2003: 1400-1405 [doi]

New results using multi array sensors and support vector machines for the detection and classification of organophosphate nerve agentsWalker H. Land Jr., Dale Leibensperger, Lut Wong, Omowunmi Sadik, A. Wanekeyab, Michiko Uematsu, Mark J. Embrechts. SMC 2003: 2883-2888 [doi]

2002

MARK: a boosting algorithm for heterogeneous kernel modelsKristin P. Bennett, Michinari Momma, Mark J. Embrechts. kdd 2002: 24-31 [doi]

Computational military tactical planning systemRobert H. Kewley, Mark J. Embrechts. tsmc, 32(2):161-171, 2002.

2001

Determining the Color-Efficiency Pareto Optimal Surface for Filtered Light SourcesNeil H. Eklund, Mark J. Embrechts. emo 2001: 603-611 [doi]

Computational intelligence for data miningMark J. Embrechts. SMC 2001: 1484 [doi]

Exploring Financial Crises Data with Self-Organizing Maps (SOM)Ismael E. Arciniegas Rueda, Betty Daniel, Mark J. Embrechts. wsom 2001: 39-46 [doi]

2000

1998

Fuzzy-genetic decision optimization for positioning of military combat unitsRobert H. Kewley, Mark J. Embrechts. SMC 1998: 3658-3663 [doi]

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2014

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1998

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