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The Fundamentals of Modern Statistical Genetics (Statistics for Biology and Health)
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent S…
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Linear Algebra and Learning from Data
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Computer Age Statistical Inference: Algorithms, Evidence, and Data Science
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Deep Learning for Vision Systems
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Statistical Pattern Recognition
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High-Dimensional Probability: An Introduction with Applications in Data Science (Cambridge Series in Statistical and Proba…
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Handbook of Polytomous Item Response Theory Models
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Statistical Methods for Pattern Recognition (Paperback)
The purpose of this book is to present some statistical methods of pattern recognition. The book brings contributions in the field of statistical pattern recognition both from a point of theoretical view and from a point of applications view which are achieved in a private field of pattern recognition: iris recognition. The book contains five chapters and four annexes.The algorithms from my book show the joining of some known results with some observations or remarks which lead to the achievement of some very general algorithms, which are suitable for solving some complex pattern problems. I shall achieve the software implementation for the project methods using the programming language Matlab 7.0. A lot of the original contributions from this book constitute the object of some meaningful papers, which are international recognized through their publication in some impressive specialty journals or books from the international and national publishing houses. My significant scientific results were published in over 20 articles appeared in prestigious national or international journals. At least 8 of my papers are well reviewed in dedicated journals. Statistical Methods for Pattern Recognition (Paperback)
Structural, Syntactic, and Statistical Pattern Recognition : Joint Iapr International Workshop, S+sspr 2014, Joensuu, Finland, August 20-22, 2014, Proceedings (Paperback)
Graph Kernels.- A Graph Kernel from the Depth-Based Representation.- Incorporating Molecule’s Stereoisomerism within the Machine Learning Framework.- Transitive State Alignment for the Quantum Jensen-Shannon Kernel.- Clustering.- Balanced K-Means for Clustering.- Poisoning Complete-Linkage Hierarchical Clustering.- A Comparison of Categorical Attribute Data Clustering Methods.- Graph Edit Distance.- Improving Approximate Graph Edit Distance Using Genetic Algorithms.- Approximate Graph Edit Distance Guided by Bipartite Matching of Bags of Walks.- A Hausdorff Heuristic for Efficient Computation of Graph Edit Distance.- Graph Models and Embedding.- Flip-Flop Sublinear Models for Graphs.- Node Centrality for Continuous-Time Quantum Walks.- Max-Correlation Embedding Computation.- Discriminant Analysis.- Fast Gradient Computation for Learning with Tensor Product Kernels and Sparse Training Labels.- Nonlinear Discriminant Analysis Based on Probability Estimation by Gaussian Mixture Model.- Combining and Selecting.- Information Theoretic Feature Selection in Multi-label Data through Composite Likelihood.- Majority Vote of Diverse Classifiers for Late Fusion.- Entropic Graph Embedding via Multivariate Degree Distributions.- On Parallel Lines in Noisy Forms.- Metrics and Dissimilarities.- Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance.- Matching Similarity for Keyword-Based Clustering.- Applications.- Quantum vs Classical Ranking in Segment Grouping.- Remove Noise in Video with 3D Topological Maps.- Video Analysis of a Snooker Footage Based on a Kinematic Model.- Partial Supervision.- Evaluating Classification Performance with only Positive and Unlabeled Samples.- Who Is Missing? A New Pattern Recognition Puzzle.- Poster Session.- Edit Distance Computed by Fast Bipartite Graph Matching.- Statistical Method for Semantic Segmentation of Dominant Plane from Remote Exploration Image Sequence.- Analyses on Generalization Error of Ensemble Kernel Regressors.- Structural Human Shape Analysis for Modeling and Recognition.- On Cross-Validation for MLP Model Evaluation.- Weighted Mean Assignment of a Pair of Correspondences Using Optimisation Functions.- Chemical Symbol Feature Set for Handwritten Chemical Symbol Recognition.- About Combining Metric Learning and Prototype Generation.- Tracking System with Re-identification Using a RGB String Kernel.- Towards Scalable Prototype Selection by Genetic Algorithms with Fast Criteria.- IOWA Operators and Its Application to Image Retrieval.- On Optimum Thresholding of Multivariate Change Detectors.- Commute Time for a Gaussian Wave Packet on a Graph.- Properties of Object-Level Cross-Validation Schemes for Symmetric Pair-Input Data.- A Binary Factor Graph Model for Biclustering.- Improved BLSTM Neural Networks for Recognition of On-Line Bangla Complex Words.- A Ranking Part Model for Object Detection.- Regular Decomposition of Multivariate Time Series and Other Matrices.- Texture Synthesis: From Convolutional RBMs to Efficient Deterministic Algorithms.- Improved Object Matching Using Structural Relations.- Designing LDPC Codes for ECOC Classification Systems.- Unifying Probabilistic Linear Discriminant Analysis Variants in Biometric Authentication. • ISBN:9783662444146 • Format:Paperback • Publication Date:2014-08-04
Lecture Notes in Computer Science: Structural, Syntactic, and Statistical Pattern Recognition: Joint Iapr International Workshop, S+sspr 2018, Beijing, China, August 17-19, 2018, Proceedings, Series No. 11004 (2018 Edition) (Paperback)
This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S]SSPR 2018, held in Beijing, China, in August 2018. The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi
and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods. • ISBN:9783319977843 • Format:Paperback • Publication Date:2018-08-02
Structural, Syntactic, and Statistical Pattern Recognition : Joint Iapr International Workshops, S+sspr 2020, Padua, Italy, January 21-22, 2021, Proceedings (Paperback)
Classification and data processing.- Deep learning.- Graph-theoretic methods.- Multimedia analysis and understanding. Structural, Syntactic, and Statistical Pattern Recognition: Joint Iapr International Workshops, S+sspr 2020, Padua, Italy, January 21-22, 2021, Proceedings (Paperback)
Springer Theses: The (Non-)Local Density of States of Electronic Excitations in Organic Semiconductors (Hardcover)
Organic Electronics in a Nutshell.- Particle-Based Models.- Long-Range Polarized Embedding of Electronic Excitations.- Charge Carriers at Organic-Organic Interfaces.- Charge Carriers in Disordered Bulk Mesophases.- Charge Transfer States at Donor-Acceptor Heterojunctions.- Conclusions \u0026 Outlook. • Author: Carl R Poelking • ISBN:9783319695983 • Format:Hardcover • Publication Date:2017-11-03
Similarity-based Pattern Recognition : Second International Workshop, Simbad 2013, York, Uk, July 3-5, 2013, Proceedings (Paperback)
Pattern Learning and Recognition on Statistical Manifolds: An Information-Geometric Review.- Dimension Reduction Methods for Image Pattern Recognition.- Efficient Regression in Metric Spaces via Approximate Lipschitz Extension.- Data Analysis of (Non-)Metric Proximities at Linear Costs.- On the Informativeness of Asymmetric Dissimilarities.- Information-Theoretic Dissimilarities for Graphs.- Information Theoretic Pairwise Clustering.- Correlation Clustering with Stochastic Labellings.- Break and Conquer: Efficient Correlation Clustering for Image Segmentation.- Multi-task Averaging via Task Clustering.- Modeling and Detecting Community Hierarchies.- Graph Characterization Using Gaussian Wave Packet Signature.- Analysis of the Schr\\u0026ouml;dinger Operator in the Context of Graph Characterization.- Attributed Graph Similarity from the Quantum Jensen-Shannon Divergence.- Entropy and Heterogeneity Measures for Directed Graphs.- Fast Learning of Gamma Mixture Models with k-MLE.- Exploiting Geometry in Counting Grids.- On the Dissimilarity Representation and Prototype Selection for Signature-Based Bio-cryptographic Systems.- A Repeated Local Search Algorithm for BiClustering of Gene Expression Data. • ISBN:9783642391392 • Format:Paperback • Publication Date:2013-07-19
