Invited Papers.- Predicting Signal Peptides with Support Vector Machines.- Scaling Large Learning Problems with Hard Parallel Mixtures.- Computational Issues.- On the Generalization of Kernel Machines.- Kernel Whitening for One-Class Classification.- A Fast SVM Training Algorithm.- Support Vector Machines with Embedded Reject Option.- Object Recognition.- Image Kernels.- Combining Color and Shape Information for Appearance-Based Object Recognition Using Ultrametric Spin Glass-Markov Random Fields.- Maintenance Training of Electric Power Facilities Using Object Recognition by SVM.- Kerneltron: Support Vector ‘Machine’ in Silicon.- Pattern Recognition.- Advances in Component-Based Face Detection.- Support Vector Learning for Gender Classification Using Audio and Visual Cues: A Comparison.- Analysis of Nonstationary Time Series Using Support Vector Machines.- Recognition of Consonant-Vowel (CV) Units of Speech in a Broadcast News Corpus Using Support Vector Machines.- Applications.- Anomaly Detection Enhanced Classification in Computer Intrusion Detection.- Sparse Correlation Kernel Analysis and Evolutionary Algorithm-Based Modeling of the Sensory Activity within the Rat’s Barrel Cortex.- Applications of Support Vector Machines for Pattern Recognition: A Survey.- Typhoon Analysis and Data Mining with Kernel Methods.- Poster Papers.- Support Vector Features and the Role of Dimensionality in Face Authentication.- Face Detection Based on Cost-Sensitive Support Vector Machines.- Real-Time Pedestrian Detection Using Support Vector Machines.- Forward Decoding Kernel Machines: A Hybrid HMM/SVM Approach to Sequence Recognition.- Color Texture-Based Object Detection: An Application to License Plate Localization.- Support Vector Machines in Relational Databases.- Multi-ClassSVM Classifier Based on Pairwise Coupling.- Face Recognition Using Component-Based SVM Classification and Morphable Models.- A New Cache Replacement Algorithm in SMO.- Optimization of the SVM Kernels Using an Empirical Error Minimization Scheme.- Face Detection Based on Support Vector Machines.- Detecting Windows in City Scenes.- Support Vector Machine Ensemble with Bagging.- A Comparative Study of Polynomial Kernel SVM Applied to Appearance-Based Object Recognition.

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