Search Results - (((((((ant OR avant) OR semantic) OR win) OR cantor) OR anne) OR shape) OR hints) algorithms.

Scalable algorithms for contact problems by Dostál, Zdeněk, Kozubek, Tomáš, 1975-, Sadowská, Marie, Vonk, Vít

Table of Contents: “…Optimal QP and QCQP Algorithms -- 5. Conjugate Gradients -- 6. Gradient Projection for Separable Convex Sets -- 7. …”
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Number, Shape, & Symmetry : an Introduction to Number Theory, Geometry, and Group Theory. by Herrmann, Diane L.

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Graph algorithms and applications 3

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Data management in the semantic web

Table of Contents: “…DATA MANAGEMENT IN THE SEMANTIC WEB ; DATA MANAGEMENT IN THE SEMANTIC WEB ; CONTENTS ; PREFACE ; INTERPRETATIONS OF THE WEB OF DATA; Abstract; 1. …”
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Metaheuristic optimization for the design of automatic control laws by Sandou, Guillaume

Table of Contents: “…Ant colony optimization…”
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Optimization of Computer Networks : Modeling and Algorithms: a Hands-On Approach. by Pavón Mariño, Pablo

Table of Contents: “…7.1 Introduction -- 7.2 Node Location Problems -- 7.3 Full Topology Design Problems -- 7.4 Multilayer Network Design -- 7.5 Notes and Sources -- 7.6 Exercises -- References -- Part Two: Algorithms -- Chapter 8: Gradient Algorithms in Network Design -- 8.1 Introduction -- 8.2 Convergence Rates -- 8.3 Projected Gradient Methods -- 8.4 Asynchronous and Distributed Algorithm Implementations -- 8.5 Non-Smooth Functions -- 8.6 Stochastic Gradient Methods -- 8.7 Stopping Criteria -- 8.8 Algorithm Design Hints -- 8.9 Notes and Sources -- 8.10 Exercises -- References…”
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Learning OWL class expressions by Lehmann, Jens, 1982-

Table of Contents: “…Refinement Operator Based OWL Learning Algorithms; OCEL (OWL Class Expression Learner); Redundancy Elimination; Creating a Full Learning Algorithm; ELTL (EL Tree Learner)…”
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Graph partitioning and graph clustering : 10th DIMACS Implementation Challenge Workshop, February 13-14, 2012, Georgia Institute of Technology, Atlanta, GA

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Natural language processing : semantic aspects by Kapetanios, Epaminondas, Tatar, Doina, 1943-, Sacarea, Christian

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Nearest-neighbor methods in learning and vision : theory and practice

Table of Contents: “…Clarkson -- Locality-sensitive hashing using stable distributions / Alexandr Andoni [and others] -- New algorithms for efficient high-dimensional nonparametric classification / Ting Liu, Andrew W. …”
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3D Shape Analysis : Fundamentals, Theory and Applications. by Tabia, Hedi

Table of Contents: “…7.2 Problem Formulation7.3 Mathematical Tools; 7.4 Isometric Correspondence and Registration; 7.5 Nonisometric (Elastic) Correspondence and Registration; 7.6 Summary and Further Reading; 8 Semantic Correspondences; 8.1 Introduction; 8.2 Mathematical Formulation; 8.3 Graph Representation; 8.4 Energy Functions for Semantic Labeling; 8.5 Semantic Labeling; 8.6 Examples; 8.7 Summary and Further Reading; Part IV: Applications; 9 Examples of 3D Semantic Applications; 9.1 Introduction; 9.2 Semantics: Shape or Status; 9.3 Semantics: Class or Identity; 9.4 Semantics: Behavior; 9.5 Semantics: Position…”
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Applications of multi-objective evolutionary algorithms

Table of Contents: “…Non-Dominated Sorting Evolution Strategy Algorithm (NSESA)3.3. Case Studies; 3.3.1. Shape Design of a Shielded Reactor; 3.3.2. …”
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Network and discrete location : models, algorithms, and applications by Daskin, Mark S., 1952-

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Computer and machine vision : theory, algorithms, practicalities by Davies, E. R. (E. Roy)

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Learning Neo4j 3.x - Second Edition. by Baton, Jerome

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Inverse Synthetic Aperture Radar Imaging with MATLAB Algorithms. by Ozdemir, Caner

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Deep Learning for the Earth Sciences : A Comprehensive Approach to Remote Sensing, Climate Science and Geosciences. by Camps-Valls, Gustau

Table of Contents: “…6.1.4 Evaluation Metrics -- 6.1.4.1 Precision-Recall Curve -- 6.1.4.2 Average Precision and Mean Average Precision -- 6.1.5 Applications -- 6.2 Preliminaries on Object Detection with Deep Models -- 6.2.1 Two-stage Algorithms -- 6.2.1.1 R-CNNs -- 6.2.1.2 R-FCN -- 6.2.2 One-stage Algorithms -- 6.2.2.1 YOLO -- 6.2.2.2 SSD -- 6.3 Object Detection in Optical RS Images -- 6.3.1 Related Works -- 6.3.1.1 Scale Variance -- 6.3.1.2 Orientation Variance -- 6.3.1.3 Oriented Object Detection -- 6.3.1.4 Detecting in Large-size Images -- 6.3.2 Datasets and Benchmark -- 6.3.2.1 DOTA -- 6.3.2.2 VisDrone…”
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Meta-heuristic and evolutionary algorithms for engineering optimization by Bozorg-Haddad, Omid, 1974-, Solgi, Mohammad, 1989-, Loaiciga, Hugo A.

Table of Contents: “…Overview of optimization -- Introduction to meta-heuristic and evolutionary algorithms -- Pattern search (PS) -- Genetic algorithm (GA) -- Simulated annealing (SA) -- Tabu search (TS) -- Ant colony optimization (ACO) -- Particle swarm optimization (PSO) -- Differential evolution (DE) -- Harmony search (HS) -- Shuffled frog-leaping algorithm (SFLA) -- Honey-bee mating optimization (HBMO) -- Invasive weed optimization (IWO) -- Central force optimization (CFO) -- Biogeography-based optimization (BBO) -- Firefly algorithm (FA) -- Gravity search algorithm (GSA) -- Bat algorithm (BA) -- Plant propagation algorithm (PPA) -- Water cycle algorithm (WCA) -- Symbiotic organisms search (SOS) -- Comprehensive evolutionary algorithm (CEA).…”
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Poems that solve puzzles : the history and science of algorithms by Bleakley, Chris

Table of Contents: “…-- Quantum Computers -- Not The End -- Appendix -- PageRank Algorithm -- Artificial Neural Network Training -- Bitcoin Algorithm -- Shor's Algorithm -- Notes -- Introduction -- Chapter 1 Ancient Algorithms -- Chapter 2 Ever-Expanding Circles…”
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Uberland : how algorithms are rewriting the rules of work by Rosenblat, Alex, 1987-

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