Hybrid Artificial Intelligence Systems
暂无分享,去创建一个
Erkki Oja | Álvaro Herrero | Emilio Corchado | Bruno Baruque | Xin-Dong Wu | E. Oja | E. Corchado | Á. Herrero | Bruno Baruque | Xindong Wu | Álvaro Herrero
[1] Andreas Hotho,et al. Tag Recommendations in Folksonomies , 2007, LWA.
[2] Alon Orlitsky,et al. Combined binary classifiers with applications to speech recognition , 2002, INTERSPEECH.
[3] R. Palmer,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[4] R. Kikinis,et al. A review of diffusion tensor imaging studies in schizophrenia. , 2007, Journal of psychiatric research.
[5] Robert P. W. Duin,et al. The combining classifier: to train or not to train? , 2002, Object recognition supported by user interaction for service robots.
[6] Robert A. Jacobs,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.
[7] Thorsten Joachims,et al. Optimizing search engines using clickthrough data , 2002, KDD.
[8] Patrick Dähne,et al. Real-Time Virtual Cables Based on Kinematic Simulation , 2000, WSCG.
[9] José Ramón Quevedo,et al. Prediction of Probability of Survival in Critically Ill Patients Optimizing the Area under the ROC Curve , 2007, IJCAI.
[10] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[11] D. Wolpert. The Supervised Learning No-Free-Lunch Theorems , 2002 .
[12] G D Pearlson,et al. Planum temporale asymmetry reversal in schizophrenia: replication and relationship to gray matter abnormalities. , 1997, The American journal of psychiatry.
[13] A.C. Campilho,et al. Combining independent and unbiased classifiers using weighted average , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.
[14] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[15] P. Basser,et al. MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.
[16] Grigorios Tsoumakas,et al. Multi-Label Classification of Music into Emotions , 2008, ISMIR.
[17] Gerardo M. Mendez,et al. Application of Interval Type-2 Fuzzy Logic Systems for Control of the Coiling Entry Temperature in a Hot Strip Mill , 2009, HAIS.
[18] E. R. Davies,et al. Machine vision - theory, algorithms, practicalities , 2004 .
[19] Karl Pearson F.R.S.. LIII. On lines and planes of closest fit to systems of points in space , 1901 .
[20] José Ramón Villar,et al. Minimizing Energy Consumption in Heating Systems under Uncertainty , 2008, HAIS.
[21] Benjamin S. Bloom,et al. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives , 2000 .
[22] Paolo Frasconi,et al. New results on error correcting output codes of kernel machines , 2004, IEEE Transactions on Neural Networks.
[23] Nageswara S. V. Rao. A Generic Sensor Fusion Problem: Classification and Function Estimation , 2004, Multiple Classifier Systems.
[24] Daoyi Dong,et al. A Quantum-inspired Q-learning Algorithm for Indoor Robot Navigation , 2008, 2008 IEEE International Conference on Networking, Sensing and Control.
[25] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[26] Dan Roth,et al. The Use of Classifiers in Sequential Inference , 2001, NIPS.
[27] Lakhmi C. Jain,et al. Designing classifier fusion systems by genetic algorithms , 2000, IEEE Trans. Evol. Comput..
[28] Robert P. W. Duin,et al. Using two-class classifiers for multiclass classification , 2002, Object recognition supported by user interaction for service robots.
[29] O. Nelles. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models , 2000 .
[30] Francisco S. Melo,et al. Reinforcement learning with function approximation for cooperative navigation tasks , 2008, 2008 IEEE International Conference on Robotics and Automation.
[31] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[32] Jason Weston,et al. A kernel method for multi-labelled classification , 2001, NIPS.
[33] G. Pearlson,et al. Sex differences in inferior parietal lobule volume in schizophrenia. , 2000, The American journal of psychiatry.
[34] Przemyslaw Kazienko,et al. Boosting Algorithm with Sequence-Loss Cost Function for Structured Prediction , 2010, HAIS.
[35] Yong Duan,et al. Fuzzy reinforcement learning and its application in robot navigation , 2005, 2005 International Conference on Machine Learning and Cybernetics.
[36] Qun Dai,et al. A competitive ensemble pruning approach based on cross-validation technique , 2013, Knowl. Based Syst..
[37] Gareth J. Barker,et al. Diffusion tensor imaging in schizophrenia , 2008, European Psychiatry.
[38] Kenneth A. Reek,et al. A software infrastructure to support introductory computer science courses , 1996, SIGCSE '96.
[39] Manuel Graña,et al. Experiments of Fast Learning with High Order Boltzmann Machines , 2004, Applied Intelligence.
[40] Christian Igel,et al. Empirical evaluation of the improved Rprop learning algorithms , 2003, Neurocomputing.
[41] J. Stanley,et al. Book Review: Taxonomy of Educational Objectives, The Classification of Educational Goals, Handbook I: Cognitive Domain , 1957 .
[42] Liwei Tian,et al. Evaluation on energy and thermal performance for residential envelopes in hot summer and cold winter zone of China , 2009 .
[43] Daw-Tung Lin,et al. Integrating a mixed-feature model and multiclass support vector machine for facial expression recognition , 2009, Integr. Comput. Aided Eng..
[44] Boguslaw Cyganek. One-Class Support Vector Ensembles for Image Segmentation and Classification , 2011, Journal of Mathematical Imaging and Vision.
[45] Silvio Simani,et al. Diagnosis techniques for sensor faults of industrial processes , 2000, IEEE Trans. Control. Syst. Technol..
[46] Manfred Männle,et al. Parameter optimization for Takagi-Sugeno fuzzy models-lessons learnt , 2001, SMC.
[47] Derek Partridge,et al. Software Diversity: Practical Statistics for Its Measurement and Exploitation | Draft Currently under Revision , 1996 .
[48] J. Scott Tyo,et al. Principal-components-based display strategy for spectral imagery , 2003, IEEE Trans. Geosci. Remote. Sens..
[49] T. Ens,et al. Blind signal separation : statistical principles , 1998 .
[50] S. Antman. Nonlinear problems of elasticity , 1994 .
[51] C. Wernicke,et al. Grundriss der Psychiatrie in klinischen Vorlesungen , 1894 .
[52] Manuel Graña,et al. The high-order Boltzmann machine: learned distribution and topology , 1995, IEEE Trans. Neural Networks.
[53] Manuel Graña,et al. Linked multi-component mobile robots: Modeling, simulation and control , 2010, Robotics Auton. Syst..
[54] Jaana Kekäläinen,et al. Cumulated gain-based evaluation of IR techniques , 2002, TOIS.
[55] Manuel Graña,et al. On the Use of Morphometry Based Features for Alzheimer's Disease Detection on MRI , 2009, IWANN.
[56] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[57] A. Agarwal,et al. Efficient Hierarchical-PCA Dimension Reduction for Hyperspectral Imagery , 2007, 2007 IEEE International Symposium on Signal Processing and Information Technology.
[58] Grigorios Tsoumakas,et al. Multi-Label Classification: An Overview , 2007, Int. J. Data Warehous. Min..
[59] Ethem Alpaydın,et al. Combined 5 x 2 cv F Test for Comparing Supervised Classification Learning Algorithms , 1999, Neural Comput..
[60] Christopher H. Brooks,et al. Improved annotation of the blogosphere via autotagging and hierarchical clustering , 2006, WWW '06.
[61] Slobodan Ribaric,et al. A knowledge-based system for the non-destructive diagnostics of façade isolation using the information fusion of visual and IR images , 2009, Expert Syst. Appl..
[62] Robert P. W. Duin,et al. Limits on the majority vote accuracy in classifier fusion , 2003, Pattern Analysis & Applications.
[63] Ian H. Witten,et al. The WEKA data mining software: an update , 2009, SKDD.
[64] Marek Kurzynski,et al. On the multistage Bayes classifier , 1988, Pattern Recognit..
[65] Przemyslaw Kazienko,et al. Prediction of Sequential Values for Debt Recovery , 2009, CIARP.
[66] Mustafa Ergen,et al. Mobile Broadband: Including WiMAX and LTE , 2010 .
[67] H. Tanaka,et al. A Formulation of Fuzzy Decision Problems with Fuzzy Information using Probability Measures of Fuzzy Events , 1978, Inf. Control..
[68] M. LeMay,et al. Abnormalities of the left temporal lobe and thought disorder in schizophrenia. A quantitative magnetic resonance imaging study. , 1992, The New England journal of medicine.
[69] Carl-Fredrik Westin,et al. DTI and MTR abnormalities in schizophrenia: Analysis of white matter integrity , 2005, NeuroImage.
[70] S. Hyakin,et al. Neural Networks: A Comprehensive Foundation , 1994 .
[71] Zyad Shaaban,et al. Data Mining: A Preprocessing Engine , 2006 .
[72] D. Tax,et al. Characterizing one-class datasets , 2006 .
[73] John Langford,et al. Search-based structured prediction , 2009, Machine Learning.
[74] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[75] Andrew McCallum,et al. Collective multi-label classification , 2005, CIKM '05.
[76] Roelof van Zwol,et al. Flickr tag recommendation based on collective knowledge , 2008, WWW.
[77] Ioannis Stamelos,et al. Open source software development should strive for even greater code maintainability , 2004, CACM.
[78] Richard J. Duro,et al. On the potential contributions of hybrid intelligent approaches to Multicomponent Robotic System development , 2010, Inf. Sci..
[79] F. Herrera,et al. A Hybrid Learning Process for the Knowledge Base of a Fuzzy Rule-Based System , 2004 .
[81] Adriana Dapena,et al. A Novel Hybrid Approach to Improve Performance of Frequency Division Duplex Systems with Linear Precoding , 2010, HAIS.
[82] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[83] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[84] Qiang Shen,et al. Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches , 2008, IEEE Press series on computational intelligence.
[85] Ekaitz Zulueta,et al. Linked Multicomponent Robotic Systems: Basic Assessment of Linking Element Dynamical Effect , 2010, HAIS.
[86] Giovanni Semeraro,et al. Recommending Smart Tags in a Social Bookmarking System , 2007 .
[87] Josef A. Nossek,et al. Transmit Wiener filter for the downlink of TDDDS-CDMA systems , 2002, IEEE Seventh International Symposium on Spread Spectrum Techniques and Applications,.
[88] Pierre Priouret,et al. Adaptive Algorithms and Stochastic Approximations , 1990, Applications of Mathematics.
[89] S. Amari,et al. Gradient Learning in Structured Parameter Spaces: Adaptive Blind Separation of Signal Sources , 1996 .
[90] G. Pearlson,et al. Decreased regional cortical gray matter volume in schizophrenia. , 1994, The American journal of psychiatry.
[91] C Barbui,et al. Cortical white-matter microstructure in schizophrenia. Diffusion imaging study. , 2007, The British journal of psychiatry : the journal of mental science.
[92] Grigorios Tsoumakas,et al. Random k -Labelsets: An Ensemble Method for Multilabel Classification , 2007, ECML.
[93] Silvio Simani,et al. Fault diagnosis of a simulated industrial gas turbine via identification approach , 2007 .
[94] Ranjit Biswas,et al. An application of intuitionistic fuzzy sets in medical diagnosis , 2001, Fuzzy Sets Syst..
[95] Andreas Hotho,et al. Trend Detection in Folksonomies , 2006, SAMT.
[96] P. Basser,et al. Diffusion tensor MR imaging of the human brain. , 1996, Radiology.
[97] Babak Hassibi,et al. Second Order Derivatives for Network Pruning: Optimal Brain Surgeon , 1992, NIPS.
[98] Manuel Graña,et al. Hierarchically structured systems , 1986 .
[99] Laurent Grisoni,et al. Geometrically exact dynamic splines , 2008, Comput. Aided Des..
[100] Viktor Kuncak,et al. Software verification and graph similarity for automated evaluation of students' assignments , 2012, Inf. Softw. Technol..
[101] Inder Jeet Taneja,et al. On the Probability of Error in Fuzzy Discrimination Problems , 1992 .
[102] Yunsong Guo,et al. Comparisons of sequence labeling algorithms and extensions , 2007, ICML '07.
[103] Hongxing Yang,et al. Investigation on the thermal performance of different lightweight roofing structures and its effect on space cooling load , 2009 .
[104] Josef Kittler,et al. Sum Versus Vote Fusion in Multiple Classifier Systems , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[105] Dias Haralambopoulos,et al. Assessing the thermal insulation of old buildings—The need for in situ spot measurements of thermal resistance and planar infrared thermography , 1998 .
[106] Andrew McCallum,et al. Maximum Entropy Markov Models for Information Extraction and Segmentation , 2000, ICML.
[107] Zelmar Echegoyen Ferreira. Contributions to visual servoing for legged and linked multicomponent robots , 2009 .
[108] Witold Pedrycz,et al. Fuzzy sets in pattern recognition: Methodology and methods , 1990, Pattern Recognit..
[109] Robert Burduk,et al. Two-stage binary classifier with fuzzy-valued loss function , 2006, Pattern Analysis and Applications.
[110] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.
[111] J. Schoukens,et al. Improved approximate identification of nonlinear systems , 2004, Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510).
[112] César Hervás-Martínez,et al. JCLEC: a Java framework for evolutionary computation , 2007, Soft Comput..
[113] Emine Yilmaz,et al. A geometric interpretation of r-precision and its correlation with average precision , 2005, SIGIR '05.
[114] Carl-Fredrik Westin,et al. The Application of DTI to Investigate White Matter Abnormalities in Schizophrenia , 2005, Annals of the New York Academy of Sciences.
[115] P. Saratchandran,et al. Multicategory Classification Using An Extreme Learning Machine for Microarray Gene Expression Cancer Diagnosis , 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[116] Urszula Stanczyk. Dominance-Based Rough Set Approach Employed in Search of Authorial Invariants , 2009, Computer Recognition Systems 3.
[117] Pedro Antonio Gutiérrez,et al. Sensitivity Versus Accuracy in Multiclass Problems Using Memetic Pareto Evolutionary Neural Networks , 2010, IEEE Transactions on Neural Networks.
[118] Przemyslaw Kazienko,et al. Hybrid Repayment Prediction for Debt Portfolio , 2009, ICCCI.
[119] Andrzej Cichocki,et al. Stability Analysis of Learning Algorithms for Blind Source Separation , 1997, Neural Networks.
[120] Cheng-Jian Lin,et al. Multiple Compensatory Neural Fuzzy Networks Fusion Using Fuzzy Integral , 2007, J. Inf. Sci. Eng..
[121] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[122] Joni-Kristian Kämäräinen,et al. Differential Evolution Training Algorithm for Feed-Forward Neural Networks , 2003, Neural Processing Letters.
[123] Brian B. Avants,et al. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..
[124] Robert P.W. Duin,et al. PRTools3: A Matlab Toolbox for Pattern Recognition , 2000 .
[125] Kaspar Althoefer,et al. Neural Network World , 2000 .
[126] A. Caprihan,et al. Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements , 2008, NeuroImage.
[127] Bartosz Krawczyk,et al. VOCs classification based on the committee of classifiers coupled with single sensor signals , 2013 .
[128] L. Sauermann,et al. ConTag : A Semantic Tag Recommendation System , 2007 .
[129] YuYong,et al. Sales forecasting using extreme learning machine with applications in fashion retailing , 2008 .
[130] L. Castedo,et al. Maximizing the information transfer for adaptive unsupervised source separation , 1997, First IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications.
[131] Grigorios Tsoumakas,et al. Multilabel Text Classification for Automated Tag Suggestion , 2008 .
[132] Gustavo E. A. P. A. Batista,et al. An analysis of four missing data treatment methods for supervised learning , 2003, Appl. Artif. Intell..
[133] Gilad Mishne,et al. AutoTag: a collaborative approach to automated tag assignment for weblog posts , 2006, WWW '06.
[134] Daniel Marcu,et al. Practical structured learning techniques for natural language processing , 2006 .
[135] ZhouZhi-Hua,et al. Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization , 2006 .
[136] R. Buchanan,et al. Brain morphology and schizophrenia. A magnetic resonance imaging study of limbic, prefrontal cortex, and caudate structures. , 1992, Archives of general psychiatry.
[137] Christian Jutten,et al. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..
[138] Sherif Hashem,et al. Optimal Linear Combinations of Neural Networks , 1997, Neural Networks.
[139] Adriana Dapena,et al. Combination of supervised and unsupervised algorithms for communication systems with linear precoding , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[140] Sunita Sarawagi,et al. Discriminative Methods for Multi-labeled Classification , 2004, PAKDD.
[141] J. M. Durand,et al. An improved decorrelation method for the efficient display of multispectral data , 1989 .
[142] Pedro Antonio Gutiérrez,et al. Multilogistic regression by evolutionary neural network as a classification tool to discriminate highly overlapping signals: Qualitative investigation of volatile organic compounds in polluted waters by using headspace-mass spectrometric analysis , 2008 .
[143] Pedro Antonio Gutiérrez,et al. Memetic Pareto Evolutionary Artificial Neural Networks to determine growth/no-growth in predictive microbiology , 2011, Appl. Soft Comput..
[144] R Kikinis,et al. Prefrontal cortex and schizophrenia. A quantitative magnetic resonance imaging study. , 1995, Archives of general psychiatry.
[145] Inés Couso,et al. Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms , 2008, Soft Comput..
[146] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[147] R Kikinis,et al. Superior temporal gyrus volume abnormalities and thought disorder in left-handed schizophrenic men. , 1999, The American journal of psychiatry.
[148] Robert A. Jacobs,et al. Methods For Combining Experts' Probability Assessments , 1995, Neural Computation.
[149] James C. Bezdek,et al. Fuzzy Kohonen clustering networks , 1994, Pattern Recognit..
[150] Kagan Tumer,et al. Analysis of decision boundaries in linearly combined neural classifiers , 1996, Pattern Recognit..
[151] Yoram Singer,et al. BoosTexter: A Boosting-based System for Text Categorization , 2000, Machine Learning.
[152] Jianchang Mao,et al. Towards the Semantic Web: Collaborative Tag Suggestions , 2006 .
[153] Emilio Corchado,et al. 1. Soft Computing for detecting thermal insulation failures in buildings , 2009 .
[154] Shigeharu Miyata,et al. Automatic Path Search for Roving Robot Using Reinforcement Learning , 2009, 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC).
[155] Sarunas Raudys,et al. Trainable fusion rules. I. Large sample size case , 2006, Neural Networks.
[156] Leandro Pardo,et al. Some bounds on probability of error in fuzzy discrimination problems , 1991 .
[157] H. Hotelling. Analysis of a complex of statistical variables into principal components. , 1933 .
[158] Francisco Rodríguez,et al. Adaptive hierarchical control of greenhouse crop production , 2008 .
[159] M. Rubin. Cosserat Theories: Shells, Rods and Points , 2000 .
[160] John Platt,et al. Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods , 1999 .
[161] Constantinos A. Balaras,et al. Infrared thermography for building diagnostics , 2002 .
[162] David S. Broomhead,et al. Multivariable Functional Interpolation and Adaptive Networks , 1988, Complex Syst..
[163] Pierre Comon,et al. Handbook of Blind Source Separation: Independent Component Analysis and Applications , 2010 .
[164] Hong Qin,et al. D-NURBS: A Physics-Based Framework for Geometric Design , 1996, IEEE Trans. Vis. Comput. Graph..
[165] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[166] R. McCarley,et al. A review of MRI findings in schizophrenia , 2001, Schizophrenia Research.
[167] Leszek Rutkowski,et al. Flexible Neuro-fuzzy Systems: Structures, Learning and Performance Evaluation (Kluwer International Series in Engineering and Computer Science) , 2004 .
[168] Jerzy W. Grzymala-Busse,et al. Handling Missing Attribute Values in Preterm Birth Data Sets , 2005, RSFDGrC.
[169] Ross D. Murch,et al. New transmit schemes and simplified receivers for MIMO wireless communication systems , 2003, IEEE Trans. Wirel. Commun..
[170] Dinggang Shen,et al. COMPARE: Classification of Morphological Patterns Using Adaptive Regional Elements , 2007, IEEE Transactions on Medical Imaging.
[171] Chee Kheong Siew,et al. Universal approximation using incremental constructive feedforward networks with random hidden nodes , 2006, IEEE Trans. Neural Networks.
[172] Lars Kai Hansen. Controlled Growth of Cascade Correlation Nets , 1994 .
[173] Carlos A. Coello Coello,et al. An updated survey of GA-based multiobjective optimization techniques , 2000, CSUR.
[174] Odile Macchi,et al. Adaptive Processing: The Least Mean Squares Approach with Applications in Transmission , 1995 .
[175] Gian Luca Marcialis,et al. Fusion of Face Recognition Algorithms for Video-Based Surveillance Systems , 2003 .
[176] Xiaohong Su,et al. Ability-training-oriented automated assessment in introductory programming course , 2011, Comput. Educ..
[177] H. Sebastian Seung,et al. The Rectified Gaussian Distribution , 1997, NIPS.
[178] Mark W. Woolrich,et al. Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.
[179] Fabio Roli,et al. A theoretical and experimental analysis of linear combiners for multiple classifier systems , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[180] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[181] László Györfi,et al. Lower Bounds for Bayes Error Estimation , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[182] Robert P. W. Duin,et al. Combining One-Class Classifiers , 2001, Multiple Classifier Systems.
[183] Stephen G. MacDonell,et al. Forensics : : old methods for a new science , 2004 .
[184] Chih-Jen Lin,et al. Trust Region Newton Method for Logistic Regression , 2008, J. Mach. Learn. Res..
[185] Sun I. Kim,et al. Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia , 2007, NeuroImage.
[186] Anil K. Jain,et al. Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[187] Kevin W. Bowyer,et al. Combination of Multiple Classifiers Using Local Accuracy Estimates , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[188] Thomas Hofmann,et al. Discriminative Learning for Label Sequences via Boosting , 2002, NIPS.
[189] Subhash C. Bagui,et al. Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.
[190] Elmar Schömer,et al. Interactive simulation of one-dimensional flexible parts , 2006, SPM '06.
[191] Hussein A. Abbass,et al. Speeding Up Backpropagation Using Multiobjective Evolutionary Algorithms , 2003, Neural Computation.
[192] Peng Wang,et al. On Classifying Disease-Induced Patterns in the Brain Using Diffusion Tensor Images , 2008, MICCAI.
[193] Zhi-Hua Zhou,et al. ML-KNN: A lazy learning approach to multi-label learning , 2007, Pattern Recognit..
[194] Grigorios Tsoumakas,et al. Effective and Efficient Multilabel Classification in Domains with Large Number of Labels , 2008 .
[195] Pedro Antonio Gutiérrez,et al. Evolutionary learning by a sensitivity-accuracy approach for multi-class problems , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[196] Ashok V. Kulkarni. On the Mean Accuracy of Hierarchical Classifiers , 1978, IEEE Transactions on Computers.
[197] Witold Pedrycz,et al. The Analysis of Software Complexity Using Stochastic Metric Selection , 2011 .
[198] P. A. Cohen. Student Ratings of Instruction and Student Achievement: A Meta-analysis of Multisection Validity Studies , 1981 .
[199] C. Frith,et al. Disordered functional connectivity in schizophrenia , 1996, Psychological Medicine.
[200] Robert Burduk,et al. Classification error in Bayes multistage recognition task with fuzzy observations , 2010, Pattern Analysis and Applications.
[201] Jiebo Luo,et al. Learning multi-label scene classification , 2004, Pattern Recognit..
[202] Dinesh K. Pai,et al. STRANDS: Interactive Simulation of Thin Solids using Cosserat Models , 2002, Comput. Graph. Forum.
[203] Louis Vuurpijl,et al. An overview and comparison of voting methods for pattern recognition , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.
[204] Timothy Edward John Behrens,et al. Characterization and propagation of uncertainty in diffusion‐weighted MR imaging , 2003, Magnetic resonance in medicine.
[205] Michael Collins,et al. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms , 2002, EMNLP.
[206] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[207] Bartosz Krawczyk,et al. Clustering-based ensembles for one-class classification , 2014, Inf. Sci..
[208] Adam Krzyżak,et al. Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..
[209] Lars Schmidt-Thieme,et al. Collaborative Tag Recommendations , 2007, GfKl.
[210] Fuad M. Alkoot. Design of multiple classifier systems , 2001 .
[211] Tomasz Walkowiak,et al. Incident Detection and Analysis in Communication and Information Systems by Fuzzy Logic , 2007, 2nd International Conference on Dependability of Computer Systems (DepCoS-RELCOMEX '07).
[212] Tom Fawcett,et al. Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions , 1997, KDD.
[213] Lutz Prechelt,et al. A Set of Neural Network Benchmark Problems and Benchmarking Rules , 1994 .
[214] Emilio Corchado,et al. 1 A soft computing based method for detecting lifetime building thermal insulation failures , 2010 .
[215] Hong Guo,et al. Neural Learning from Unbalanced Data , 2004, Applied Intelligence.
[216] B. Turetsky,et al. Reduced dorsal and orbital prefrontal gray matter volumes in schizophrenia. , 2000, Archives of general psychiatry.
[217] Inés Couso,et al. Higher order models for fuzzy random variables , 2008, Fuzzy Sets Syst..
[218] H. Abbass,et al. PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[219] N. Makris,et al. Cortical abnormalities in schizophrenia identified by structural magnetic resonance imaging. , 1999, Archives of general psychiatry.
[220] D. Godard,et al. Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems , 1980, IEEE Trans. Commun..
[221] B. Ripley,et al. Pattern Recognition , 1968, Nature.
[222] L. Zadeh. Probability measures of Fuzzy events , 1968 .
[223] James C. Bezdek,et al. Decision templates for multiple classifier fusion: an experimental comparison , 2001, Pattern Recognit..
[224] Iven M. Y. Mareels,et al. Advantages of smooth trajectory tracking as crane anti-swing schemes , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.
[225] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[226] F. López-Granados,et al. Structural Simplification of Hybrid Neuro-Logistic Regression Models in Multispectral Analysis of Remote Sensed Data , 2008 .
[227] Hadar I. Avi-Itzhak,et al. Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[228] R. McCarley,et al. Abnormal angular gyrus asymmetry in schizophrenia. , 2000, The American journal of psychiatry.
[229] Lotfi A. Zadeh,et al. Soft computing and fuzzy logic , 1994, IEEE Software.
[230] Emilio Corchado,et al. A survey of multiple classifier systems as hybrid systems , 2014, Inf. Fusion.