الصفحة 64
الصفحة 64
Machine Learning: ECML 2006 ; 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings
This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held in Berlin, Germany in September 2006, jointly with PKDD 2006. The 46 revised full papers and 36 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 564 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
Machine Learning, Image Processing, Network Security and Data Sciences ; 2nd International conference, MIND 2020, Silchar, India, July 30 - 31, 2020, Proceedings, Part II
This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cyber security.
Machine learning, image processing, network security and data sciences ; 2nd International conference, MIND 2020, Silchar, India, July 30 - 31, 2020, Proceedings, Part I
This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cyber security.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine learning methods for reverse engineering of defective structured surfaces
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Machine Learning for Multimodal Interaction ; Vol.4299 ; 3rd International Workshop, MLMI 2006, Bethesda, MD, USA, May 1-4, 2006, Revised Selected Papers
This book contains a selection of refereed papers presented at the 3rd Workshop on Machine Learning for Multimodal Interaction (MLMI 2006), held in Bethesda MD, USA during May 1–4, 2006.
Machine Learning for Multimodal Interaction ; Vol.3361 : 1st International Workshop, MLMI 2004, Martigny, Switzerland, June 21-23, 2004, Revised Selected Papers
his book contains a selection of refereed papers presented at the 1st Wo- shop on Machine Learning for Multimodal Interaction (MLMI 2004), held at the “Centre du Parc,” Martigny, Switzerland, during June 21–23, 2004. The workshop was organized and sponsored jointly by three European projects, – AMI, Augmented Multiparty Interaction, http://www.amiproject.org – PASCAL, Pattern Analysis, Statistical Modeling and Computational Learning, http://www.pascal-network.org – M4, Multi-modal Meeting Manager, http://www.m4project.org as well as the Swiss National Centre of Competence in Research (NCCR): – IM2: Interactive Multimodal Information Management, http://www.im2.ch MLMI 2004 was thus sponsored by the European Commission and the Swiss National Science Foundation.
Machine Learning for Multimodal Interaction ; 5th International Workshop, MLMI 2008, Utrecht, The Netherlands, September 8-10, 2008. Proceedings
The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.
Machine Learning for Cyber Agents : Attack and Defence
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.
Machine learning challenges : Evaluating predictive uncertainty, Visual Object Classification, and Recognizing Textual Entailment, 1st Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
Constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.
Machine Learning and Knowledge Extraction ; 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, Virtual Event, August 17–20, 2021, Proceedings
Constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II
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.
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I
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.
Machine learning and data mining for sports analytics ; 7th international workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.
Lymphocyte Trafficking in Health and Disease
Since the discovery of chemokines and of chemokine receptors it has become evident that expression of chemokines at the site of inflammation may regulate the composition of cellular infiltrate, thereby directing the type of immune response. Recently, the molecular characterization of inherited disorders of immune system, (e.g., Wiskott-Aldrich syndrome, WHIM syndrome, leukocyte adhesion deficiency), which are characterized by cytoskeleton/adhesion defects or by altered response of chemokine receptors has contributed to clarifying the key players of immune response in normal physiology and in disease. This book, which deals with the description of the role of chemokines in immune response and underlines potential targets of therapeutical intervention, offers a series of contributions of the most challenging aspects of lymphocyte migration in homeostasis and in disease.
Lung Pathology
Learning the diagnostic elements of lung pathology requires not only great familiarity with a wide diversity of cases, but also a sharp eye for analyzing pictorial images. In Lung Pathology: A Consultative Atlas, leading experts offer a novel and substantive approach to the teaching of pulmonary pathology. Drawing on 263 challenging, yet exemplary, referral cases taken from files collected over 20 years by internationally renowned lung pathologist, Dr. Eugene Mark, the authors introduce his state-of-the-art approach to the interpretation of pulmonary pathology. This text includes the primary and/or differential diagnosis and the pertinent histological features of each case, as well as clinical history, when available. Key words or phrases in the text are highlighted and digitally hyperlinked to associated images or regions of interest within those images to assist the readers in their correlation. Novel and user friendly, Lung Pathology: A Consultative Atlas describes a cutting-edge diagnostic approach to pulmonary pathology, describing its principles and demonstrating its application in text and full-color illustrations drawn from 263 difficult cases of human lung pathologies.
Long-Term Preservation of Digital Documents : Principles and Practices
Key to our culture is that we can disseminate information, and then maintain and access it over time. While we are rapidly advancing from vulnerable physical solutions to superior, digital media, preserving and using data over the long term involves complicated research challenges and organization efforts. Uwe Borghoff and his coauthors address the problem of storing, reading, and using digital data for periods longer than 50 years. They briefly describe several markup and document description languages like TIFF, PDF, HTML, and XML, explain the most important techniques such as migration and emulation, and present the OAIS (Open Archival Information System) Reference Model. To complement this background information on the technology issues the authors present the most relevant international preservation projects, such as the Dublin Core Metadata Initiative, and experiences from sample projects run by the Cornell University Library and the National Library of the Netherlands. A rated survey list of available systems and tools completes the book.
Longs COVID-19 patients
Nearly 250 million people around the world have recovered from Covid-19. But here, the word "recovered" refers only to the acute phase of the illness. Approximately 10 and 40 percent of Covid patients continue to experience symptoms several weeks to months after falling sick, a nebulous condition now referred to as post-Covid condition, or long Covid. In long Covid, we are witnessing the emergence of a legitimate new illness, officially recognized by the World Health Organization's International Classification of Diseases...
Long-Run Growth Forecasting
Explores how to set up an empirical model that helps with forecasting long-term economic growth in a large number of countries. It offers a systematic approach to models of potential GDP that can also be used for forecasts of more than a decade. It is an attempt to fill the wide gap between the high demand for such models by commercial banks, international organizations, central banks and governments on the one hand and the limited supply on the other hand. Frequent forecast failures in the past (e.g. Japan 1990, Asia 1997) and the heavy economic losses they produced motivated the work. The book assesses the large number of different theories of economic growth, the drivers of economic growth, the available datasets and the empirical methods on offer. A preference is shown for evolutionary models and an augmented Kaldor model. The book uses non-stationary panel techniques to find pair-wise cointegration among GDP per capita and its main correlates such as physical capital, human capital and openness.
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
