Preface; Contents; Applications of Machine Learning; Maximum Likelihood Estimation and Optimal Coordinates; 1 Introduction; 2 Entropy and Gaussian Random Variables; 3 Rescaling; 4 Main Result; 5 Conclusion; References; Domain Adaptation for Image Analysis: An Unsupervised Approach Using Boltzmann Machines Trained by Perturbation; 1 Introduction; 2 Unsupervised Domain Adaptation Problem; 3 Boltzmann Machines; 4 Perturb-and-MAP Learning Algorithm; 5 Experiments; 6 Discussion and Conclusion; References; Relation Recognition Problems and Algebraic Approach to Their Solution; Abstract

1 Introduction2 Basic Notions; 3 Solution of Simple and Extended RR Problems; 4 Solution of Matching RR Problems; 5 Solution of Constructive RR Problems; 6 The CRR Problem; 7 Conclusions; Acknowledgement; References; Prediction of Power Load Demand Using Modified Dynamic Weighted Majority Method; Abstract; 1 Introduction; 2 Related Work; 3 Proposed Method; 3.1 Modified Dynamic Weighted Majority Method; 3.2 Dynamic Weighted Majority with Decomposition; 3.3 Technical Issues; 3.4 Optimization of Parameters by Particle Swarm Optimization; 4 Evaluation; 4.1 Data Description; 5 Conclusion

AcknowledgementsReferences; Estimating Cluster Population; Abstract; 1 Introduction; 2 Review of Existing Approaches; 3 Estimation of Cluster Population; 3.1 Preliminaries; 3.2 Adaptive Bucketing; 3.3 Aggregating Bucket Clusters; 3.4 Nudging; 4 Results and Discussion; References; Evaluation of Particle Swarm Optimisation for Medical Image Segmentation; 1 Introduction; 2 Overview of PSO-Based Algorithms; 2.1 Particle Swarm Optimisation (PSO); 2.2 Darwinian Particle Swarm Optimisation (DPSO); 2.3 Fractional Order Darwinian Particle Swarm Optimisation (FODPSO); 3 Experimental Work

3.1 Segmentation of Brain in MRI Images3.2 Volume Reconstruction; 3.3 Automatic Editing of CT Images; 4 Conclusion; References; Automated Processing of Micro-CT Scans Using Descriptor-Based Registration of 3D Images; 1 Introduction; 2 Problem Statement; 3 Materials and Methods; 4 Results and Discussion; 5 Conclusion; References; Gender Recognition Based on Speaker's Voice Analysis; 1 Introduction; 2 Algorithm Description; 3 Summary and Conclusions; References; Topic Modeling Based on Frequent Sequences Graphs; 1 Introduction; 2 Topic Modeling Methods; 3 Methodology; 3.1 Method Overview

3.2 Building Frequent N-grams3.3 Finding Significant Edges; 3.4 Topic Modeling; 4 Experiment Results and Discussion; 5 Concluding Remarks and Future Research; References; Gaussian Process Regression with Categorical Inputs for Predicting the Blood Glucose Level; 1 Introduction; 2 Methodology; 2.1 Gaussian Process Regression Model; 2.2 Prediction; 2.3 Learning; 3 Experiment; 3.1 Data Description; 3.2 Experiment Details; 3.3 Results and Discussion; 4 Conclusion; References; Automated Information Extraction and Classification of Matrix-Based Questionnaire Data; 1 Introduction