الصفحة 14
الصفحة 14
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
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 Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine learning and big data : Concepts, algorithms, tools and applications
Showcase novel use-cases and applications, present empirical research results from user-centered qualitative and quantitative experiments of these new applications, and facilitate a discussion forum to explore the latest trends in big data and machine learning by providing algorithms which can be trained to perform interdisciplinary techniques such as statistics, linear algebra, and optimization and also create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention
Machine Learning Algorithms Using Python Programming
Presents the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning.
Machine Learning : ECML 2005 ; 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings
The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qualified independent reviews per paper (with very few exceptions) and one additional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall.
Louisiana's response to extreme weather : A coastal state's adaptation challenges and successes
Takes an in-depth look at Louisiana as a state which is ahead of the curve in terms of extreme weather events, both in frequency and magnitude, and in its responses to these challenges including recovery and enhancement of resiliency.
Location- and Context-Awareness ; Vol. 3479 ; First International Workshop, LoCA 2005, Oberpfaffenhofen, Germany, May 12-13, 2005, Proceedings
The workshop was organized by the Institute of Communications and Navigation of the German Aerospace Center (DLR) in Oberpfa?enhofen, and the Mobile and Distributed Systems Group of the University of Munich. During the workshop, novel positioning algorithms and location sensing techniques were discussed, comprising not only enhancements of singular systems, like positioning in GSM or WLAN, but also hybrid technologies, such as the integration of global satellite systems with inertial positioning. Furthermore, improvements in sensor technology, as well as the integration and fusion of sensors, were addressed both on a theoretical and on an implementation level. Personal and confidential data, such as location data of users, have p- found implications for personal information privacy. Thus privacy protection, privacy-oriented location-aware systems, and how privacy aspects the feasibility and usefulness of systems were also addressed in the workshop.
Liver carcinogenesis : Methods and protocols
Discusses the latest advancements in modern methodologies used to study liver carcinogenesis. The first half of this book describes pertinent preclinical models of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), established either through orthotopic induction of ectopic implantation. The second half of this book covers a diverse array of techniques applied to characterize the biochemical and cellular composition of hepatic malignancies that operate at the single-cell and histological levels. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
LINQ for Visual C# 2008
Every C# programmer needs to learn about LINQ (Language–Integrated Query), Microsoft's breakthrough technology for simplifying and unifying data access from any data source. With LINQ, you can write more elegant and flexible code—not just to access databases and files, but to manipulate data structures and XML. This book is a short, yet comprehensive guide to the major features of LINQ and the significant enhancements introduced with .NET 3.5. There is no better source for getting a head–start on the future of these technologies than this book.
LINQ for Visual C# 2005
LINQ for Visual C# 2005 is a short, yet comprehensive guide to the major features of LINQ. It thoroughly covers LINQ to Objects, LINQ to SQL, LINQ to DataSet, and LINQ to XML. It also details significant enhancements to C#, .NET, and ADO.NET.
Limits to the European Union’s Normative Power in a Post-conflict Society : EULEX and Peacebuilding in Kosovo
Investigates the EU’s peacebuilding activities in that country, in the light of the normative power theory in the post-conflict setting and peacebuilding theory. Ten years after the massive engagement of the EU in the country torn by war, the authors critically assess the effects of the EU projecting its normative power – the enforcement of its standards, ‘good’ or ‘bad’ – through the EULEX mission, taking into consideration also the local aspects, so far neglected in this field of research. Inspecting thoroughly the EULEX activities in the police, customs and judiciary sector.This open access book offers a comprehensive assessment of the EULEX mission, based on two Horizon2020 research projects: IECEU - Improving the Effectiveness of Capabilities in EU Conflict Prevention, and KOSNORTH – The European Union and its Normative Power in a Post-conflict Society: A Case Study of Northern Kosovo (Marie Sklodowska-Curie Individual Fellowship).
Les prothèses tricompartimentaires du genou de première intention : Techniques opératoires. Problèmes et solutions = Primary tricompartmental knee replacement : Surgical techniques, problems, and solutions
It seems difficult and presumptuous to want to write a book on total knee replacement. There are many quality works dealing with this subject. The knee prosthesis has, from its origin, particularly in the United States, given rise to considerable studies in all directions: biomechanical, physiological, biological and industrial. Our goal is to offer the youngest a book of simple knowledge without pretension of completeness or prejudice as to long debated subjects (conservation or not of the posterior cruciate ligament, cement or without cement, resurfacing or not of the patella, fixed plate or mobile platform, etc.), and to give practical advice based on our experience. Why limit yourself to first-line tricompartmentals? Because it is the most common solution to the usual degenerative knee problems. In addition, unicompartment and revision prostheses will be the subject of further literature. Everyone knows that to put a knee prosthesis model, and therefore to a system. However, it is important to be able to keep your freedom of analysis in order to maintain your freedom of choice. You have to know how to put on a knee prosthesis without compromise or fanaticism. Convictions are more dangerous enemies of truth than lies. Nietzsche
Legitimacy in International Law
In recent years the question of the legitimacy of international law has been discussed quite intensively. Such questions are, for example, whether international law lacks legitimacy in general; whether international law or a part of it has yielded to the facts of power; whether adherence to international legal commitments should be subordinated to self-defined national interests; whether international law or particular rules of it – such as the prohibition of the use of armed force – have lost their ability to induce compliance (compliance pull); and what is the relevance of non-enforcement or failure to obey for the legitimacy of that particular international norm? This book contains fresh perspectives on these questions, offered at an international and interdisciplinary conference hosted by the Max Planck Institute for Comparative Law and International Law.
Learning Theory ; Vol. 4005 ; 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, Proceedings
Constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA in June 2006. The 43 revised full papers presented together with 2 articles on open problems and 3 invited lectures were carefully reviewed and selected from a total of 102 submissions. The papers cover a wide range of topics including clustering, un- and semisupervised learning, statistical learning theory, regularized learning and kernel methods, query learning and teaching, inductive inference, learning algorithms and limitations on learning, online aggregation, online prediction and reinforcement learning.
Learning Theory ; Vol. 3559 : 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, Proceedings
The technical program contained 45 papers selected from 120 submissions, 3 open problems selected from among 5 contributed, and 2 invited lectures. The invited lectures were given by Sergiu Hart on “Uncoupled Dynamics and Nash Equilibrium”, and by Satinder Singh on “Rethinking State, Action, and Reward in Reinforcement Learning”. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. The student selected this year was Hadi Salmasian for the paper titled “The Spectral Method for General Mixture Models” co-authored with Ravindran Kannan and Santosh Vempala. The number of papers submitted to COLT this year was exceptionally high. In addition to the classical COLT topics, we found an increase in the number of submissions related to novel classi?cation scenarios such as ranking. This - crease re?ects a healthy shift towards more structured classi?cation problems, which are becoming increasingly relevant to practitioners.
Learning theory ; 20th Annual Conference on Learning theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007, Proceedings
It covers unsupervised, semisupervised and active learning, statistical learning theory, inductive inference, regularized learning, kernel methods, SVM, online and reinforcement learning, learning algorithms and limitations on learning, dimensionality reduction, as well as open problems.
Learning from nature how to design new implantable biomaterialsis : From biomineralization fundamentals to biomimetic materials and processing routes ; Proceedings of the NATO Advanced Study Institute, held in Alvor, Algarve, Portugal, 13-24 October 2003
The demands upon the material properties largely depend on the site of application and the function it has to restore. Ideally, a replacement material should mimic the living tissue from a mechanical, chemical, biological and functional point of view.
Learning and Adaption in Multi-Agent Systems ; 1st International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers
Contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?
