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Dancing with Qubits
Unlock the core math and understand the technical nuances of quantum computing in this detailed guide. Delve into the practicality of NISQ algorithms, and survey promising advancements in quantum machine learning. Key Features Discover how quantum computing works and delve into the math behind it with practical examples Learn about and assess the most up-to-date quantum computing topics including quantum machine learning Explore the inner workings of existing quantum computing technologies to understand how they may perform significantly better than their classical counterparts Book DescriptionDancing with Qubits, Second Edition, is a comprehensive quantum computing textbook that starts with...
Pattern Recognition and Data Mining
The two volume set LNCS 3686 and LNCS 3687 constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The first volume includes 73 contributions related to Pattern Recognition and Data Mining (which included papers from the tracks of pattern recognition methods, knowledge and learning, and data mining); topics addressed are pattern recognition, data mining, signal processing and OCR/ document analysis. The second volume contains 87 contributions related to Pattern Recognition and Image Analysis (which included papers from the applications track) and deals with security and surveillance, biometrics, image processing and medical imaging. It also contains papers from the Workshop on Pattern Recognition for Crime Prevention.
Services Management in Intelligent Networks
This book constitutes the refereed proceedings of the 11th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management, DSOM 2000, held in Austin, TX, USA in December 2000. The 21 revised full papers presented were carefully reviewed and selected from a total of 65 submissions. The book is divided into topical sections on architectures for internet management, fault management of services and networks, inter-domain management, event handling for management services, QoS management, and management architectures.
Management Research Methodology
The subject of management research methodology is enthralling and complex. A student or a practitioner of management research is beguiled by uncertainties in the search and identification of the research problem, intrigued by the ramifications of research design, and confounded by obstacles in obtaining accurate data and complexities of data analysis. Management Research Methodology: Integration of Principles, Methods and Techniques seeks a balanced treatment of all these aspects and blends problem-solving techniques, creativity aspects, mathematical modelling and qualitative approaches in order to present the subject of Management Research Methodology in a lucid and easily understandable way.
Data Mining for Business Applications
Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications.
Advances in Data Mining: Applications and Theoretical Aspects
These are the proceedings of the tenth event of the Industrial Conference on Data Mining ICDM held in Berlin (www.data-mining-forum.de). For this edition the Program Committee received 175 submissions. After the pe- review process, we accepted 49 high-quality papers for oral presentation that are included in this book. The topics range from theoretical aspects of data mining to app- cations of data mining such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society. Extended versions of selected papers will appear in the international journal Trans- tions on Machine Learning and Data Mining (www.ibai-publis...
Sparse Modeling
Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing. Sparse Modeling: Theory, Algorithms, and Applications provides an introduction to the growing field of sparse modeling, including application examples, problem formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery. The book gets you up to speed on the latest sparsity-related developments and will motivate you to continue learning about the field. The...
Advances in Data Mining - Theoretical Aspects and Applications
The papers in this volume represent the proceedings of the 7th Industrial Conference on Data Mining. They are organized into topical sections on aspects of classification and prediction, clustering, web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Readers gain new insights into theories underlying data mining and discover state-of-the-technology applications.
Advances on Data Mining: Applications and Theoretical Aspects
This book constitutes the refereed proceedings of the 11th Industrial Conference on Data Mining, ICDM 2011, held in New York, USA in September 2011. The 22 revised full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and in telecommunication, Multimedia Data Mining, theoretical aspects of data mining, Data Warehousing, WebMining and Information Mining.
Advances in Knowledge Discovery and Data Mining
This book constitutes the refereed proceedings of the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China, May 2007. It covers new ideas, original research results and practical development experiences from all KDD-related areas including data mining, machine learning, data warehousing, data visualization, automatic scientific discovery, knowledge acquisition and knowledge-based systems.
