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Record Nr. |
UNINA9910300251103321 |
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Titolo |
Gems of combinatorial optimization and graph algorithms / / edited by Andreas S. Schulz, Martin Skutella, Sebastian Stiller, Dorothea Wagner |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (153 p.) |
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Disciplina |
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Soggetti |
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Operations research |
Management science |
Algorithms |
Calculus of variations |
Game theory |
Convex geometry |
Discrete geometry |
Combinatorial analysis |
Operations Research, Management Science |
Calculus of Variations and Optimal Control; Optimization |
Game Theory, Economics, Social and Behav. Sciences |
Convex and Discrete Geometry |
Combinatorics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Shifting Segments to Optimality: Stefan Felsner -- Linear structure of graphs and the knotting graph: Ekkehard Köhler -- Finding Longest Geometric Tours: Sandor P. Fekete -- Generalized Hanan Grids for Geometric Steiner Trees in Uniform Orientation Metrics: Matthias Müller-Hannemann -- Budgeted Matching via the Gasoline Puzzle: Guido Schäfer -- Motifs in Networks: Karsten Weihe -- Graph Fill-In, Elimination Ordering, Nested Dissection and Contraction Hierarchies: Ben Strasser and Dorothea Wagner -- Shortest Path To Mechanism Design: Rudolf Müller and Marc Uetz -- Selfish Routing and |
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Proportional: Resource Allocation: Andreas S. Schulz -- Resource Buying Games: Tobias Harks and Britta Peis -- Linear, exponential, but nothing else - On pure Nash equilibria in congestion games and priority rules for single-machine scheduling: Max Klimm -- Convex quadratic programming in scheduling: Martin Skutella -- Robustness and approximation for universal sequencing: Nicole Megow -- A Short Note on Long Waiting Lists: Sebastian Stiller. |
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Sommario/riassunto |
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Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory? Maybe you need a convenient source of relevant, current topics for a graduate student or advanced undergraduate student seminar? Or perhaps you just want an enjoyable look at some beautiful mathematical and algorithmic results, ideas, proofs, concepts, and techniques in discrete mathematics and theoretical computer science? Gems of Combinatorial Optimization and Graph Algorithms is a handpicked collection of up-to-date articles, carefully prepared by a select group of international experts, who have contributed some of their most mathematically or algorithmically elegant ideas. Topics include longest tours and Steiner trees in geometric spaces, cartograms, resource buying games, congestion games, selfish routing, revenue equivalence and shortest paths, scheduling, linear structures in graphs, contraction hierarchies, budgeted matching problems, and motifs in networks. This volume is aimed at readers with some familiarity of combinatorial optimization, and appeals to researchers, graduate students, and advanced undergraduate students alike. |
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2. |
Record Nr. |
UNINA9910983388103321 |
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Autore |
Schlippe Tim |
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Titolo |
Artificial Intelligence in Education Technologies: New Development and Innovative Practices : Proceedings of 2024 5th International Conference on Artificial Intelligence in Education Technology / / edited by Tim Schlippe, Eric C. K. Cheng, Tianchong Wang |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (588 pages) |
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Collana |
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Lecture Notes on Data Engineering and Communications Technologies, , 2367-4520 ; ; 228 |
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Altri autori (Persone) |
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ChengEric C. K |
WangTianchong |
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Disciplina |
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Soggetti |
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Education - Data processing |
Educational technology |
Natural language processing (Computer science) |
Artificial intelligence |
Education - Research |
Data mining |
Computers and Education |
Digital Education and Educational Technology |
Natural Language Processing (NLP) |
Artificial Intelligence |
Research Methods in Education |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Emerging AI Technologies, Methods, Systems, and Infrastructure -- Innovative Practices of Teaching and Assessment Driven by AI and Education Technologies -- Curriculum, Teacher Professional Development and Policy for AI in Education -- Issues and Discussions on AI In Education and Future Development. |
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Sommario/riassunto |
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This book is a collection of selected research papers presented at the |
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2024 5th International Conference on Artificial Intelligence in Education Technology (AIET 2024), held in Barcelona, Spain, on July 29 - 31, 2024. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. It is a timely and up-to-date publication responsive to the rapid development of AI technologies, practices and their increasingly complex interplay with the education domain. It promotes the cross-fertilisation of knowledge and ideas from researchers in various fields to construct the interdisciplinary research area of AI in Education. These subject areas include computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology and linguistics. The feature of this book will contribute from diverse perspectives to form a dynamic picture of AI in Education. It also includes various domain-specific areas for which AI and other education technology systems have been designed or used in an attempt to address challenges and transform educational practice. Education stands as a cornerstone for societal progress, and ensuring universal access to quality education is integral to achieving Goal 4 of the United Nations' Sustainable Development Goals (SDGs). The goal is to ensure inclusive and equitable quality education for all by 2030. This involves not only expanding access to education but also improving the quality of education to promote lifelong learning opportunities. AI has the potential to significantly contribute to the achievement of Goal 4. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education, and triggering an exponential leap towards the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education. |
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