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الصفحة 90
Adaptive Multimedia Retrieval : User, Context, and Feedback ; Third International Workshop, AMR 2005, Glasgow, UK, July 28-29, 2005, Revised Selected Papers
This book is an extended collection of revised contributions that were initially submitted to the International Workshop on Adaptive Multimedia Retrieval (AMR 2005). This workshop was organized during July 28-29, 2005, at the U- versity of Glasgow, UK, as part of an information retrieval research festival and in co-location with the 19th International Joint Conference on Arti?cial Int- ligence (IJCAI 2005). AMR 2005 was the third and so far the biggest event of the series of workshops that started in 2003 with a workshop during the 26th German Conference on Arti?cial Intelligence (KI 2003) and continued in 2004 as part of the 16th European Conference on Arti?cial Intelligence (ECAI 2004).
Adaptive Machine Learning Algorithms with Python : Solve Data Analytics and Machine Learing Problems on Edge Devices
Learn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use. You will: Apply adaptive algorithms to practical applications and examples / Understand the relevant data representation features and computational models for time-varying multi-dimensional data / Derive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real data / Speed up your algorithms and put them to use on real-world stationary and non-stationary data / Master the applications of adaptive algorithms on critical edge device computation applications
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
Adaptive Business Intelligence
In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.
Adaptive Autonomous Secure Cyber Systems
Establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment.
Adaptive and natural computing algorithms ; Proceedings of the International Conference in Coimbra, Portugal, 2005
The ICANNGA series of Conferences has been organised since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientific community and is a reference for established workers in this area.and this book about Proceedings of the International Conference in Coimbra, Portugal, 2005 including Topics Artificial Intelligence Simulation and Modeling / Mathematics of Computing / Computer Applications
Adaptive and Natural Computing Algorithms ; 8th International Conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007, Proceedings, Part II
The ICANNGA series of conferences has been organized since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientifc community. the ICANNGA series has established itself as a reference for scientists and practitioners in this area. The series has also been of value to young researchers wishing both to extend their knowledge and experience and to meet experienced professionals in their ?elds. In a rapidly advancing world, where technology and engineering change d- matically, new challenges in computer science compel us to broaden the c- ference scope in order to take into account new developments.
Adaptive and Natural Computing Algorithms ; 8th International Conference, ICANNGA 2007, Warsaw, Poland, April 11-14, 2007, Proceedings, Part I
Constitutes the refereed proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007, held in Warsaw, Poland, in April 2007. The 178 revised full papers presented were carefully reviewed and selected from a total of 474 submissions. The 94 papers of the first volume are organized in topical sections on evolutionary computation, genetic algorithms, particle swarm optimization, learning, optimization and games, fuzzy and rough systems, just as classification and clustering. The second volume contains 84 contributions related to neural networks, support vector machines, biomedical signal and image processing, biometrics, computer vision, as well as to control and robotics.
Adaptive agents and multi-agent systems III : Adaptation and multi-Agent learning ; 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS).
Adaptive agents and multi-agent systems II : Adaptation and multi-agent learning
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Adapting Proofs-as-Programs : The Curry--Howard Protocol
This book nuds new things to do with an old idea. The proofs-as-programs paradigm constitutes a set of approaches to developing programs from proofs in constructive logic. there is increasingly active research in applying constructive techniques to industrial-scale, complex software engineering problems. Thismonographdetailsseveralimportantadvancesinthisdirectionofpr- tical proofs-as-programs. One of the central themes of the book is a general, abstract framework for developing new systems of program synthesis by adapting proofs-as-programs to new contexts. Framework-oriented approaches that facilitate analogous - proaches to building systems for solving particular problems have been popular and successful. Thesemethodsarehelpful asthey providea formal toolbox that enablesa“roll-your-own”approachtodevelopingsolutions.Itishopedthatour framework will have a similar impact. The framework is demonstrated by example. We will give two novel - plications of proofs-as-programs to large-scale, coarse-grain software engine- ing problems: contractual imperative program synthesis and structured p- gram synthesis.
Ada 2005 Rationale : The Language, The Standard Libraries
The primary goals for this book were to enhance its capabilities particularly in those areas where its reliability and predictability are of great value. Accordingly, a number of intriguing and attractive ideas have been included and implemented in a coherent manner as appropriate to the level of perfection necessary for the diligent maintenance of a language standard.
Active mining ; 2nd International workshop, AM 2003, Maebashi, Japan, October 28, 2003, revised selected papers
"This volume contains the papers selected for presentation at the 2nd Inter- tional Workshop on Active Mining (AM 2003) which was organized in conju- tion with the 14th International Symposium on Methodologies for Intelligent Systems (ISMIS 2003), The workshop was organized by the Maebashi Institute of Technology for shed light on the future development of active mining. "This volume contains : Topics Database Management / Artificial Intelligence / Algorithm Analysis and Problem Complexity / Health Informatics / Bioinformatics
Active Lighting and Its Application for Computer Vision : 40 Years of History of Active Lighting Techniques
Computer vision entails both passive and active illumination techniques. Whereas passive techniques observe the scene statically and analyse it as is, by contrast active techniques give the scene some actions and try to facilitate the analysis. In particular, active illumination techniques project specific light, for which the characteristics are known beforehand, to a target scene to enable stable and accurate analysis of the scene.
Active Conceptual Modeling of Learning : Next Generation Learning-Base System Development
This volume contains a collection of the papers presented during the 1st International ACM-L Workshop, which was held on November 8, 2006 during the 25th International Conference on Conceptual Modeling, ER 2006, held November 6–9,2006, in Tucson, Arizona, plus several invited papers.These papers plus the invited papers represent the current thinking in conceptual modeling research, The active model can only be realized through technology integration (e.g., AI, software engineering, information technology,cognitive science, art and sciences, philosophy, etc.)
Accessing Multilingual Information Repositories ; 6th Workshop of the Cross-Language Evaluation Forum, CLEF 2005, Vienna, Austria, 21-23 September, 2005, Revised Selected Papers
The sixth campaign of the Cross Language Evaluation Forum (CLEF) for European languages was held from January to September 2005. CLEF is by now an established international evaluation initiative and 74 groups from all over the world submitted results for one or more of the different evaluation tracks in 2005, compared with 54 groups in 2004. There were eight distinct evaluation tracks, designed to test the performance of a wide range of systems for multilingual information access. Full details regarding the design of the tracks, the methodologies used for evaluation, and the results obtained by the participants can be found in the different sections of these proceedings.
Accessible access 2003
In that book we tried very hard not to simply list everything that we knew about the product. Instead we tried to act as intelligent filters, presenting only the essential information that you need to get started. Every screen shot has been retaken and every section has been re-checked to ensure, not only that it still works, but also that it is actually still relevant. We have re-written parts where the product has changed and also added some. For example, there is a new section on Object Dependencies and a whole new chapter about Data Access Pages - helping you to put your Access database onto an intranet.
Abstraction, Reformulation, and Approximation ; 7th International Symposium, SARA 2007, Whistler, Canada, July 18-21, 2007, Proceedings
This volume contains the proceedings of SARA 2007, the seventh symposium, held at Whistler Village, British Columbia, Canada, July 18-21. Three distinguished speakers were invited to give keynote presentations, and their abstracts are included herein,It has been recognized since the inception of artificial intelligence that abstractions, problem reformulations and approximations (AR&A) are central to human common-sense reasoning and problem solving and to the ability of systems to reason effectively in complex domains.AR&A techniques have been used in a variety of problem-solving settings, including automated reasoning, cognitive modelling.
Abstraction, refinement and proof for probabilistic systems
Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important. Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic—but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar "assertional" style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.
Abstract Computing Machines : A Lambda Calculus Perspective
The book addresses ways and means of organizing computations, highlighting the relationship between algorithms and the basic mechanisms and runtime structures necessary to execute them using machines. It completely abstracts from concrete programming languages and machine architectures, taking instead the lambda calculus as the basic programming and program execution model to design various abstract machines for its correct implementation. The emphasis is on fully normalizing machines based on full-fledged beta-reductions as essential prerequisites for symbolic computations that treat functions and variables truly as first-class objects. Their weakly normalizing counterparts are shown to be functional abstract machines that sacrifice the flavors of full beta-reductions for decidedly simpler runtime structures and improved runtime efficiency. Further downgrading of the lambda calculus leads to classical imperative machines that permit side-effecting operations on the runtime environment.
