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Towards a New Evolutionary Computation
Estimation of Distribution Algorithms (EDAs) are a set of algorithms in the Evolutionary Computation (EC) field characterized by the use of explicit probability distributions in optimization. Contrarily to other EC techniques such as the broadly known Genetic Algorithms (GAs) in EDAs, the crossover and mutation operators are substituted by the sampling of a distribution previously learnt from the selected individuals. EDAs have experienced a high development that has transformed them into an established discipline within the EC field. This book attracts the interest of new researchers in the EC field as well as in other optimization disciplines, and that it becomes a reference for all of us working on this topic. The twelve chapters of this book can be divided into those that endeavor to set a sound theoretical basis for EDAs, those that broaden the methodology of EDAs and finally those that have an applied objective.
The New Avenues in Bioinformatics
Bioinformatics has ignited the imagination of scientists, entrepreneurs and the general public. At the meeting place of two fast growth disciplines, biology and computer science Bioinformatics is one of the cornerstones of the new biology. It is clearly pivotal to the translation of high throughput projects such the human genome project into useful knowledge. Yet despite all this attention, there is no consensus on what exactly is Bioinformatics. There are several canonical topics, such as gene structure prediction, protein functional classification or structure prediction. The present book explores new frontiers in bioinformatics, such as Glycomics or the computational modeling of genetic p...
Application of Cytometry in Primary Immunodeficiencies
We acknowledge the initiation and support of this Research Topic by the International Union of Immunological Societies (IUIS). We hereby state publicly that the IUIS has had no editorial input in articles included in this Research Topic, thus ensuring that all aspects of this Research Topic are evaluated objectively, unbiased by any specific policy or opinion of the IUIS.
Artificial Intelligence and Machine Learning
This book contains a selection of the best papers of the 31st Benelux Conference on Artificial Intelligence, BNAIC 2019, and 28th Belgian Dutch Machine Learning Conference, BENELEARN 2019, held in Brussels, Belgium in November 2019. The 11 papers presented in this volume were carefully reviewed and selected from 50 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.
Genome Evolution
In the years since the publication of Susumu Ohno's 1970 landmark book Evolution by gene duplication tremendous advances have been made in molecular biology and especially in genomics. Studies of genome structure and function prerequisite to testing hypotheses of genome evolution were all but impossible until recent methodological advances. This book evaluates newly generated empirical evidence as it pertains to theories of genomic evolutionary patterns and processes. Tests of hypotheses using analyses of complete genomes, interpreted in a phylogenetic context, provide evidence regarding the relative importance of gene duplication. The alternative explanation is that the evolution of regulatory elements that control the expression of and interactions among genes has been a more important force in shaping evolutionary innovation. This collection of papers will be of interest to all academic and industry researchers working in the fields of molecular biology, biotechnology, genomics and genome centers.
Bioinformatics and Biomedical Engineering
This volume constitutes the proceedings of the 9th International Work-Conference on IWBBIO 2020, held in Maspalomas, Gran Canaria, Spain, in June 2022. The total of 75 papers presented in the proceedings, was carefully reviewed and selected from 212 submissions. The papers cover the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine.
Machine Learning and Knowledge Discovery in Databases
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Pattern Classification Using Ensemble Methods
1. Introduction to pattern classification. 1.1. Pattern classification. 1.2. Induction algorithms. 1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian methods. 1.6. Other induction methods -- 2. Introduction to ensemble learning. 2.1. Back to the roots. 2.2. The wisdom of crowds. 2.3. The bagging algorithm. 2.4. The boosting algorithm. 2.5. The AdaBoost algorithm. 2.6. No free lunch theorem and ensemble learning. 2.7. Bias-variance decomposition and ensemble learning. 2.8. Occam's razor and ensemble learning. 2.9. Classifier dependency. 2.10. Ensemble methods for advanced classification tasks -- 3. Ensemble classification. 3.1. Fusions methods. 3.2. Selecting classification. 3.3. Mixture...
Advances in Visual Computing
The two volume set LNCS 8887 and 8888 constitutes the refereed proceedings of the 10th International Symposium on Visual Computing, ISVC 2014, held in Las Vegas, NV, USA. The 74 revised full papers and 55 poster papers presented together with 39 special track papers were carefully reviewed and selected from more than 280 submissions. The papers are organized in topical sections: Part I (LNCS 8887) comprises computational bioimaging, computer graphics; motion, tracking, feature extraction and matching, segmentation, visualization, mapping, modeling and surface reconstruction, unmanned autonomous systems, medical imaging, tracking for human activity monitoring, intelligent transportation systems, visual perception and robotic systems. Part II (LNCS 8888) comprises topics such as computational bioimaging , recognition, computer vision, applications, face processing and recognition, virtual reality, and the poster sessions.
