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Computational Methods of Feature Selection by Huan Liu,Hiroshi Motoda Pdf
Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Encyclopedia of Machine Learning by Claude Sammut,Geoffrey I. Webb Pdf
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Artificial Intelligence and Bioinspired Computational Methods by Radek Silhavy Pdf
This book gathers the refereed proceedings of the Artificial Intelligence and Bioinspired Computational Methods Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Artificial intelligence and bioinspired computational methods now represent crucial areas of computer science research. The topics presented here reflect the current discussion on cutting-edge hybrid and bioinspired algorithms and their applications.
Advanced Computational Methods for Knowledge Engineering by Thanh Binh Nguyen,Tien van Do,Hoai An Le Thi,Ngoc Thanh Nguyen Pdf
This proceedings consists of 20 papers which have been selected and invited from the submissions to the 4th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2016) held on 2-3 May, 2016 in Laxenburg, Austria. The conference is organized into 5 sessions: Advanced Optimization Methods and Their Applications, Models for ICT applications, Topics on discrete mathematics, Data Analytic Methods and Applications and Feature Extractio, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering. The editors hope that this volume can be useful for graduate and Ph.D. students and researchers in Applied Sciences, Computer Science and Applied Mathematics.
Advanced Computational Methods for Knowledge Engineering by Hoai An Le Thi,Ngoc Thanh Nguyen,Tien Van Do Pdf
This volume contains the extended versions of papers presented at the 3rd International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2015) held on 11-13 May, 2015 in Metz, France. The book contains 5 parts: 1. Mathematical programming and optimization: theory, methods and software, Operational research and decision making, Machine learning, data security, and bioinformatics, Knowledge information system, Software engineering. All chapters in the book discuss theoretical and algorithmic as well as practical issues connected with computation methods & optimization methods for knowledge engineering and machine learning techniques.
Computational Methods by G.R. Liu,V.B.C. Tan,X. Han Pdf
The First International Conference on Computational Methods (ICCM04), organized by the department of Mechanical Engineering, National University of Singapore, was held in Singapore, December 15-17, 2004, with great success. This conference proceedings contains some 290 papers from more than 30 countries/regions. The papers cover a broad range of topics such as meshfree particle methods, Generalized FE and Extended FE methods, inverse analysis and optimization methods. Computational methods for geomechanics, machine learning, vibration, shock, impact, health monitoring, material modeling, fracture and damage mechanics, multi-physics and multi-scales simulation, sports and environments are also included. All the papers are pre-reviewed before they are accepted for publication in this proceedings. The proceedings will provide an informative, timely and invaluable resource for engineers and scientists working in the important areas of computational methods.
Computational Methods in Inferring Cancer Tissue-of-Origin and Cancer Molecular Classification, Volume I by Min Tang,Cheng Guo,Ling Kui,Shuai Cheng Li,Jialiang Yang Pdf
Advances in Computational Techniques for Biomedical Image Analysis by Deepika Koundal,Savita Gupta Pdf
Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems. Covers various challenges and common research issues related to biomedical image analysis Describes advanced computational approaches for biomedical image analysis Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization Explores cloud based medical imaging together with medical imaging security and forensics
Computational Methods for Molecular Imaging by Fei Gao,Kuangyu Shi,Shuo Li Pdf
This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers from academia and industry up to date on the most recent developments in this field.
Computational Methods and Data Engineering by Vijayan K. Asari,Vijendra Singh,Rajkumar Rajasekaran,R. B. Patel Pdf
The book features original papers from International Conference on Computational Methods and Data Engineering (ICCMDE 2021), organized by School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India, during November 25–26, 2021. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of advanced computing.
Advancement of Intelligent Computational Methods and Technologies by O.P. Verma,Seema Verma,Thinagaran Perumal Pdf
The compiled volume originates from the notable contributions presented at the 1st International Conference on Advancementof Intelligent Computational Methods and Technologies (AICMT2023), which took place in a hybrid format on June 27, 2023,at Delhi Technical Campus, Greater Noida, Uttar Pradesh, India. This comprehensive collection serves as an exploration into the dynamic domain of intelligent computational methods and technologies, offering insights into the latest and upcoming trends in computation methods. AICMT2023’s scope encompasses the evolutionary trajectory of computational methods, addressing pertinent issues in real time implementation, delving into the emergence of new intelligent technologies, exploring next-generation problem-solving methodologies, and other interconnected areas. The conference is strategically designed to spotlight current research trendswithin the field, fostering a vibrant research culture and contributing to the collective knowledge base.
Advanced Computational Methods for Knowledge Engineering by Nguyen-Thinh Le,Tien van Do,Ngoc Thanh Nguyen,Hoai An Le Thi Pdf
These proceedings consist of 19 papers, which have been peer-reviewed by international program committee and selected for the 5th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2017), which was held on June 30–July 1, 2017 in Berlin, Germany. The respective chapters discuss both theoretical and practical issues in connection with computational methods and optimization methods for knowledge engineering. The broad range of application areas discussed includes network computing, simulation, intelligent and adaptive e-learning, information retrieval, sentiment analysis, autonomous underwater vehicles, social media analysis, natural language processing, biomimetics in organizations, and cash management. In addition to pure content, the book offers many inspiring ideas and suggests new research directions, making it a valuable resource for graduate students, Ph.D. students, and researchers in Computer Science and Applied Mathematics alike.
Feature Engineering and Selection by Max Kuhn,Kjell Johnson Pdf
The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.
Computational Methods for the Analysis of Genomic Data and Biological Processes by Francisco A. Gómez Vela,Federico Divina,Miguel García-Torres Pdf
In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.
