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Machine Learning and Knowledge Discovery in Databases
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.
High Performance Computing for Computational Science -- VECPAR 2014
This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on High Performance Computing for Computational Science, VECPAR 2014, held in Eugene, OR, USA, in June/July 2014. The 25 papers presented were carefully reviewed and selected of numerous submissions. The papers are organized in topical sections on algorithms for GPU and manycores, large-scale applications, numerical algorithms, direct/hybrid methods for solving sparse matrices, performance tuning. The volume also contains the papers presented at the 9th International Workshop on Automatic Performance Tuning.
Machine Learning and Knowledge Discovery in Databases
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.
Inductive Logic Programming
"How often we recall, with regret", wrote Mark Twain about editors, "that Napoleon once shot at a magazine editor and missed him and killed a publisher. But we remember with charity, that his intentions were good. " Fortunately, we live in more forgiving times, and are openly able to express our pleasure at being the editors of this volume containing the papers selected for presentation at the 14th International Conference on Inductive Logic Programming. ILP 2004 was held in Porto from the 6th to the 8th of September, under the auspices of the Department of Electrical Engineering and Computing of the Faculty of Engineering of the University of Porto (FEUP), and the Laborat ́ orio de Intelig...
Hybrid Quantum Metaheuristics
The reference text introduces the principles of quantum mechanics to evolve hybrid metaheuristics-based optimization techniques useful for real world engineering and scientific problems. The text covers advances and trends in methodological approaches, theoretical studies, mathematical and applied techniques related to hybrid quantum metaheuristics and their applications to engineering problems. The book will be accompanied by additional resources including video demonstration for each chapter. It will be a useful text for graduate students and professional in the field of electrical engineering, electronics and communications engineering, and computer science engineering, this text: Discusses quantum mechanical principles in detail. Emphasizes the recent and upcoming hybrid quantum metaheuristics in a comprehensive manner. Provides comparative statistical test analysis with conventional hybrid metaheuristics. Highlights real-life case studies, applications, and video demonstrations.
Multiprocessor Execution of Logic Programs
Addresses the efficient implementation of logic programming languages, specifically PROLOG, on multiprocessor architectures. Develops approaches and implementations aimed at taking full advantage of sequential implementation technology developed for PROLOG while exploiting all forms of control parallelism present in logic programs. Covers the analysis of parallel execution models, combining independent and-parallelism and or-parallelism, and extensions and variations of the and-or model. Annotation copyright by Book News, Inc., Portland, OR
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