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ORCID9. MCS 2010: Cairo, Egypt
- Neamat El Gayar, Josef Kittler, Fabio Roli:
Multiple Classifier Systems, 9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010. Proceedings. Lecture Notes in Computer Science 5997, Springer 2010, ISBN 978-3-642-12126-5
Classifier Ensembles(I)
- Santi Seguí
, Laura Igual, Jordi Vitrià:
Weighted Bagging for Graph Based One-Class Classifiers. 1-10 - Muhammad Atif Tahir, Josef Kittler, Krystian Mikolajczyk, Fei Yan:
Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers. 11-21 - Ahmed Salah El-Din, Neamat El Gayar:
New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization. 22-32 - Gregory Ditzler, Michael D. Muhlbaier, Robi Polikar:
Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC. 33-42 - David Windridge:
Tomographic Considerations in Ensemble Bias/Variance Decomposition. 43-53 - Ludmila I. Kuncheva, Catrin O. Plumpton:
Choosing Parameters for Random Subspace Ensembles for fMRI Classification. 54-63
Classifier Ensembles(II)
- Juan José Rodríguez, César Ignacio García-Osorio, Jesús Maudes, José-Francisco Díez-Pastor:
An Experimental Study on Ensembles of Functional Trees. 64-73 - Battista Biggio, Giorgio Fumera, Fabio Roli:
Multiple Classifier Systems under Attack. 74-83 - Francesco Gargiulo, Carlo Sansone:
SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning. 84-93 - Giulia Troglio, Marina Alberti, Jón Atli Benediktsson, Gabriele Moser, Sebastiano B. Serpico, Einar Stefánsson:
Unsupervised Change-Detection in Retinal Images by a Multiple-Classifier Approach. 94-103 - Víctor Soto, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez:
A Double Pruning Algorithm for Classification Ensembles. 104-113 - Krzysztof Kryszczuk, Paul Hurley:
Estimation of the Number of Clusters Using Multiple Clustering Validity Indices. 114-123
Classifier Diversity
- Gavin Brown, Ludmila I. Kuncheva:
"Good" and "Bad" Diversity in Majority Vote Ensembles. 124-133 - Zhi-Hua Zhou, Nan Li:
Multi-information Ensemble Diversity. 134-144
Classifier Selection
- Paulo Rodrigo Cavalin, Robert Sabourin, Ching Y. Suen:
Dynamic Selection of Ensembles of Classifiers Using Contextual Information. 145-154 - Wan-Jui Lee, Robert P. W. Duin, Horst Bunke:
Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems. 155-164
Combining Multiple Kernels
- Alexander Tatarchuk, Eugene Urlov, Vadim Mottl, David Windridge:
A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities. 165-174 - Fei Yan, Krystian Mikolajczyk, Josef Kittler, Muhammad Atif Tahir:
Combining Multiple Kernels by Augmenting the Kernel Matrix. 175-184
Boosting and Bootstrapping
- Raymond S. Smith, Terry Windeatt:
Class-Separability Weighting and Bootstrapping in Error Correcting Output Code Ensembles. 185-194 - Oriol Pujol:
Boosted Geometry-Based Ensembles. 195-204 - Adam Craig Pocock, Paraskevas Yiapanis, Jeremy Singer, Mikel Luján, Gavin Brown:
Online Non-stationary Boosting. 205-214
Handwriting Recognition
- Volkmar Frinken, Andreas Fischer, Horst Bunke:
Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting. 215-224 - Mohamed Farouk Abdel Hady, Friedhelm Schwenker:
Combining Committee-Based Semi-supervised and Active Learning and Its Application to Handwritten Digits Recognition. 225-234 - Nabiha Azizi, Nadir Farah, Mokhtar Sellami, Abdel Ennaji:
Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition. 235-244
Applications
- Waleed M. Azmy, Amir F. Atiya, Hisham El-Shishiny:
Forecast Combination Strategies for Handling Structural Breaks for Time Series Forecasting. 245-253 - Farhad Samadzadegan, Behnaz Bigdeli, Pouria Ramzi:
A Multiple Classifier System for Classification of LIDAR Remote Sensing Data Using Multi-class SVM. 254-263 - Luana Batista, Eric Granger, Robert Sabourin:
A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation. 264-273 - Noha A. Yousri:
A Multi-objective Sequential Ensemble for Cluster Structure Analysis and Visualization and Application to Gene Expression. 274-283 - Carlo Sansone, Vincenzo Paduano, Michele Ceccarelli:
Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells. 284-293 - Matteo Re, Giorgio Valentini:
An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction. 294-303 - Mahmoud Khademi, Mohammad Taghi Manzuri Shalmani, Mohammad Hadi Kiapour, Ali Akbar Kiaei:
Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network. 304-313
Invited Papers
- Gavin Brown:
Some Thoughts at the Interface of Ensemble Methods and Feature Selection. 314 - Friedhelm Schwenker, Stefan Scherer, Miriam Schmidt, Martin Schels, Michael Glodek:
Multiple Classifier Systems for the Recogonition of Human Emotions. 315-324
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