Sarunas Raudys

发表

Evolution and generalization of a single neurone: I. Single-layer perceptron as seven statistical classifiers

Sarunas Raudys, S. Raudys, 1998, Neural Networks.

Multiclass Mineral Recognition Using Similarity Features and Ensembles of Pair-Wise Classifiers

Sarunas Raudys, Rimantas Kybartas, Nurdan Akhan Baykan, 2010, IEA/AIE.

Experts' Boasting in Trainable Fusion Rules

Sarunas Raudys, S. Raudys, 2003, IEEE Trans. Pattern Anal. Mach. Intell..

Three decision making levels in portfolio management

Aistis Raudys, Sarunas Raudys, S. Raudys, 2012, 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Aging in Artificial Learning Systems

Sarunas Raudys, S. Raudys, 2007, ECAL.

On the accuracy of a bootstrap estimate of the classification error

Sarunas Raudys, 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

Prior weights in adaptive pattern classification

Sarunas Raudys, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Multi-agent System Approach to React to Sudden Environmental Changes

Sarunas Raudys, Antanas Mitasiunas, S. Raudys, 2007, MLDM.

On Dimensionality, Sample Size, Classification Error, and Complexity of Classification Algorithm in Pattern Recognition

Sarunas Raudys, Vitalijus Pikelis, S. Raudys, 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Scaled rotation regularization

Sarunas Raudys, S. Raudys, 2000, Pattern Recognit..

Classifiers Fusion in Recognition of Wheat Varieties

Sarunas Raudys, A. A. Bielskis, Ömer Kaan Baykan, 2007, MCS.

Variable selection with neural networks

Patrick Gallinari, Sarunas Raudys, Françoise Fogelman-Soulié, 1996, Neurocomputing.

Generalization Error of Randomized Linear Zero Empirical Error Classifier: Simple Asymptotics for Centered Data Case

Sarunas Raudys, Valdas Diciunas, S. Raudys, 2000, Informatica.

Determination of optimal dimensionality in statistical pattern classification

Sarunas Raudys, 1979, Pattern Recognit..

K-nearest Neighbors Directed Noise Injection in Multilayer Perceptron Training

Robert P. W. Duin, Sarunas Raudys, Marina Skurichina, 2000, IEEE Trans. Neural Networks Learn. Syst..

Statistical and Neural Classifiers

Sarunas Raudys, S. Raudys, 2001, Advances in Pattern Recognition.

Expected error of minimum empirical error and maximal margin classifiers

Sarunas Raudys, Valdas Diciunas, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Taxonomy of Classifiers Based on Dissimilarity Features

Sarunas Raudys, S. Raudys, 2005, ICAPR.

Linear classifiers in perceptron design

Sarunas Raudys, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Comparison of Two Classification Methodologies on a Real-World Biomedical Problem

Sarunas Raudys, Richard Baumgartner, Ray L. Somorjai, 2002, SSPR/SPR.

Multi-agent system based on oscillating agents for portfolio design

Aistis Raudys, Sarunas Raudys, Darius Plikynas, 2014, 2014 14th International Conference on Intelligent Systems Design and Applications.

Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners

Anil K. Jain, Sarunas Raudys, S. Raudys, 1991, IEEE Trans. Pattern Anal. Mach. Intell..

Integration of Statistical and Neural Methods to Design Classifiers in Case of Unequal Covariance Matrices

Sarunas Raudys, 2004, KI.

Collective selection of the best version of a pattern recognition system

Sarunas Raudys, Vitalijus Pikelis, S. Raudys, 1982, Pattern Recognit. Lett..

First-Order Tree-Type Dependence between Variables and Classification Performance

Sarunas Raudys, Ausra Saudargiene, 2001, IEEE Trans. Pattern Anal. Mach. Intell..

Classifier's Complexity Control while Training Multilayer Perceptrons

Sarunas Raudys, 2000, SSPR/SPR.

Multicategory Nets of Single-Layer Perceptrons: Complexity and Sample-Size Issues

Edmundas Kazimieras Zavadskas, Sarunas Raudys, Rimantas Kybartas, 2010, IEEE Transactions on Neural Networks.

Multi-stage nonlinear classification of respiratory sounds

Sarunas Raudys, Yasemin P. Kahya, Emin Çagatay Güler, 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

A Pool of Classifiers by SLP: A Multi-class Case

Sarunas Raudys, Antanas Andrius Bielskis, Vitalij Denisov, 2006, ICIAR.

Multiple Classification Systems in the Context of Feature Extraction and Selection

Sarunas Raudys, 2002, Multiple Classifier Systems.

Yerkes-Dodson Law in Agents' Training

Sarunas Raudys, Viktoras Justickis, 2003, EPIA.

The Multi-Agent System for Prediction of Financial Time Series

Sarunas Raudys, Indre Zliobaite, 2006, ICAISC.

Multiple Classifiers System for Reducing Influences of Atypical Observations

Masakazu Iwamura, Sarunas Raudys, 2004, Multiple Classifier Systems.

Evolution and generalization of a single neurone. III. Primitive, regularized, standard, robust and minimax regressions

Sarunas Raudys, S. Raudys, 2000, Neural Networks.

Portfolio of Automated Trading Systems: Complexity and Learning Set Size Issues

Sarunas Raudys, S. Raudys, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Expected classification error of the Fisher linear classifier with pseudo-inverse covariance matrix

Robert P. W. Duin, Sarunas Raudys, S. Raudys, 1998, Pattern Recognit. Lett..

A Price We Pay for Inexact Dimensionality Reduction

Vytautas Valaitis, Sarunas Raudys, Gene Biziuleviciene, 2015, IWBBIO.

Reduction of the Boasting Bias of Linear Experts

Sarunas Raudys, Arunas Janeliunas, 2002, Multiple Classifier Systems.

Structures of Covariance Matrix in Handwritten Character Recognition

Masakazu Iwamura, Sarunas Raudys, 2004, SSPR/SPR.

Prediction of Commodity Prices in Rapidly Changing Environments

Sarunas Raudys, Indre Zliobaite, 2005, ICAPR.

Regularization by Early Stopping in Single Layer Perceptron Training

Sarunas Raudys, Tautvydas Cibas, 1996, ICANN.

Intrinsic dimensionality and small sample properties of classifiers

Sarunas Raudys, 1998, Kybernetika.

Effect of Synthetic Emotions on Agents' Learning Speed and Their Survivability

Sarunas Raudys, 2005, ECAL.

Two-stage classi cation of respiratory sound patterns

Bülent Sankur, Sarunas Raudys, Yasemin P. Kahya, 2003 .

Survival of Intelligent Agents in Changing Environments

Sarunas Raudys, 2004, ICAISC.

Trainable fusion rules. I. Large sample size case

Sarunas Raudys, S. Raudys, 2006, Neural Networks.

Evolution and generalization of a single neurone: : II. Complexity of statistical classifiers and sample size considerations

Sarunas Raudys, S. Raudys, 1998, Neural Networks.

Pairwise Costs in Multiclass Perceptrons

Aistis Raudys, Sarunas Raudys, S. Raudys, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Target Value Control While Training the Perceptrons in Changing Environments

Sarunas Raudys, S. Raudys, 2008, 2008 Fourth International Conference on Natural Computation.

Biologically Inspired Architecture of Feedforward Networks for Signal Classification

Minija Tamosiunaite, Sarunas Raudys, 2000, SSPR/SPR.

Feature Over-Selection

Sarunas Raudys, 2006, SSPR/SPR.

Fixed Non-linear Combining Rules versus Adaptive Ones

Sarunas Raudys, Zidrina Pabarskaite, 2004, ICAISC.

Functional Model of Criminality: Simulation Study

Sarunas Raudys, Aini Hussain, Arunas Augustinaitis, 2005, CONTEXT.

Evolution of Multi-class Single Layer Perceptron

Sarunas Raudys, 2007, ICANNGA.

An Experimental Comparison of Fixed and Trained Fusion Rules for Crisp Classifier Outputs

Gian Luca Marcialis, Fabio Roli, Sarunas Raudys, 2002, Multiple Classifier Systems.

Variable Selection with Optimal Cell Damage

Patrick Gallinari, Sarunas Raudys, Tautvydas Cibas, 1994 .

On Dimensionality, Sample Size, and Classification Error of Nonparametric Linear Classification Algorithms

Sarunas Raudys, S. Raudys, 1997, IEEE Trans. Pattern Anal. Mach. Intell..

Social Organization of Evolving Multiple Classifier System Functioning in Changing Environments

Sarunas Raudys, 2007, ICANNGA.

The Behavior Knowledge Space Fusion Method: Analysis of Generalization Error and Strategies for Performance Improvement

Fabio Roli, Sarunas Raudys, 2003, Multiple Classifier Systems.

Reducing the Overconfidence of Base Classifiers when Combining Their Decisions

Sarunas Raudys, Richard Baumgartner, Ray L. Somorjai, 2003, Multiple Classifier Systems.

Group Interests of Agents Functioning in Changing Environments

Sarunas Raudys, Alvydas Pumputis, 2005, CEEMAS.

How good are support vector machines?

Sarunas Raudys, 2000, Neural Networks.

Sample Size Issues in the Choice between the Best Classifier and Fusion by Trainable Combiners

Aistis Raudys, Giorgio Fumera, Sarunas Raudys, 2014, IDEAL.

On Understanding and Assessing Feature Selection Bias

Sarunas Raudys, Richard Baumgartner, Ray L. Somorjai, 2005, AIME.

Multi-agent system based portfolio management in prior-to-crisis and crisis period

Aistis Raudys, Sarunas Raudys, Zidrina Pabarskaite, 2012, 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA).

Generalization Error of Multinomial Classifier

Sarunas Raudys, 2006, SSPR/SPR.

Modelling of Excitation Propagation for Social Interactions

Aistis Raudys, Sarunas Raudys, Darius Plikynas, 2014, HCI.

Structures of the Covariance Matrices in the Classifier Design

Sarunas Raudys, Ausra Saudargiene, 1998, SSPR/SPR.

High frequency trading portfolio optimisation: Integration of financial and human factors

Aistis Raudys, Sarunas Raudys, S. Raudys, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Trainable fusion rules. II. Small sample-size effects

Sarunas Raudys, 2006, Neural Networks.

Dynamically Controlled Length of Training Data for Sustainable Portfolio Selection

Aistis Raudys, Sarunas Raudys, Zidrina Pabarskaite, 2018, Sustainability.