الصفحة 56
الصفحة 56
Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms : A Practical Approach Using Python
Describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies.
Advanced data mining and applications ; Vol. 4093 : 2nd International Conference, ADMA 2006, Xi'an, China, August 14-16, 2006, Proceedings
This book constitutes the refereed proceedings of the Second International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China in August 2006. The 41 revised full papers and 74 revised short papers presented together with 4 invited papers were carefully reviewed and selected from 515 submissions. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, text mining, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, security and privacy issues, spatial data mining, and streaming data mining.
Advanced data mining and applications ; Vol. 3584 ; 1st International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Proceedings
This book constitutes the refereed proceedings of the First International Conference on Advanced Data Mining and Applications, ADMA 2005, held in Wuhan, China in July 2005. The 25 revised full papers and 75 revised short papers presented were carefully peer-reviewed and The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, text mining, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, security and privacy issues, spatial data mining, and streaming data mining.
Advanced Data Mining and Applications ; 4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008. Proceedings
This book constitutes the refereed proceedings of the 4th International Conference on Advanced Data Mining and Applications, ADMA 2008, held in Chengdu, China, in October 2008.
Advanced Data Mining and Applications ; 3rd International Conference, ADMA 2007, Harbin, China, August 6-8, 2007 Proceedings
The Third International Conference on Advanced Data Mining and Applications (ADMA) organized in Harbin, China continued the tradition already established by the first two ADMA conferences in Wuhan in 2005 and Xi’an in 2006. One major goal of ADMA is to create a respectable identity in the data mining research com- nity. This feat has been partially achieved in a very short time despite the young age of the conference, thanks to the rigorous review process insisted upon, the outstanding list of internationally renowned keynote speakers and the excellent program each year. The impact of a conference is measured by the citations the conference papers receive. Some have used this measure to rank conferences.
Advanced Concepts for Intelligent Vision Systems ; Vol. 4179 ; 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006, Proceedings
This book constitutes the refereed proceedings of the 8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006, held in Antwerp, Belgium in September 2006. The 45 revised full papers and 65 revised poster papers presented were carefully reviewed and selected from around 242 submissions. The papers are organized in topical sections on noise reduction and restoration, segmentation, motion estimation and tracking, video processing and coding, camera calibration, image registration and stereo matching, biometrics and security, medical imaging, image retrieval and image understanding, as well as classification and recognition.
Advanced Concepts for Intelligent Vision Systems ; 9th International Conference, ACIVS 2007, Delft, The Netherlands, August 28-31, 2007, Proceedings
This volume collects the papers accepted for presentation at the Ninth International Conference on “Advanced Concepts for Intelligent Vision Systems”The ACIVS conference was established in 1999 in Baden-Baden (Germany) as part of a large m ulticonference. Since then ACIVS has been developed as an independent scientific event and has maintained the tradition of being a single track event with oral presentations of 25 minutes each, even though the number of participants has been steadily growing every year. The conference currently attracts computer scientists from more than 20 countries, mostly from Europe, Australia and Japan, but also from the USA, Asia and the Middle East.
Advanced Algorithms and Data Structures
introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms
Advance Concepts of Image Processing and Pattern Recognition : Effective Solution for Global Challenges
Explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc.
Ad-Hoc, mobile, and wireless networks ; Vol.3738 ; 4th International conference, ADHOC-NOW 2005, Cancun, Mexico, October 6-8, 2005, Proceedings
This book constitutes the refereed proceedings of the 4th International Conference on Ad-Hoc Networks and Wireless, ADHOiNOW 2005, The papers discuss architectures, protocols, and algorithms for: access control, scheduling, ad hoc and sensor networks analytic methods and modelling for performance evaluation, characterization, optimization, auto-configuration, incentives and pricing, location awareness, discovery, dependence, and management, mesh networks, new applications, power management, power control, and energy-efficiency, quality-of-service, resource allocation, multimedia, routing (unicast, multicast, etc.), security and privacy, service discovery, systems and testbeds, wireless internet, and data management.
Ad-hoc, Mobile and Wireless Networks ; 7th International Conference, ADHOC-NOW 2008 Sophia-Antipolis, France, September 10-12, 2008 Proceedings
This book constitutes the refereed proceedings of the 7th International Conference on Ad-Hoc, Mobile, and Wireless Networks, ADHOC-NOW 2008, held in Sophia-Antipolis, France, September 2008.
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 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.
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
Accelerator Programming Using Directives ; 6th International Workshop, WACCPD 2019, Denver, CO, USA, November 18, 2019, Revised Selected Papers
This book constitutes the refereed post-conference proceedings of the 6th International Workshop on Accelerator Programming Using Directives, WACCPD 2019, held in Denver, CO, USA, in November 2019. The 7 full papers presented have been carefully reviewed and selected from 13 submissions. The papers share knowledge and experiences to program emerging complex parallel computing systems. They are organized in the following three sections: porting scientific applications to heterogeneous architectures using directives; directive-based programming for math libraries; and performance portability for heterogeneous architectures.
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.
