Search Results - (((((((ant OR wante) OR semantic) OR arte) OR cantor) OR anne) OR wartin) OR hints) algorithms.

Genome Sequencing Technology and Algorithms. by Kim, Sun

Full text (MFA users only)

Pattern Recognition. by Theodoridis, Sergios

Table of Contents: “…Chapter 13 Clustering Algorithms II: Hierarchical AlgorithmsChapter 14 Clustering Algorithms III: Schemes Based on Function Optimization; Chapter 15 Clustering Algorithms IV; Chapter 16 Cluster Validity; Appendix A Hints from Probability and Statistics; Appendix B Linear Algebra Basics; Appendix C Cost Function Optimization; Appendix D Basic Definitions from Linear Systems Theory; Index.…”
Full text (MFA users only)

Graph algorithms and applications 3

Full text (MFA users only)

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. …”
Full text (MFA users only)

Metaheuristic optimization for the design of automatic control laws by Sandou, Guillaume

Table of Contents: “…Ant colony optimization…”
Full text (MFA users only)

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…”
Full text (MFA users only)

Learning OWL class expressions by Lehmann, Jens, 1982-

Table of Contents: “…Preliminaries and State of the Art; Semantic Web; History and Vision; RDF and SPARQL; Description Logics; OWL; Concept Learning and Inductive Reasoning; History, Tools, and Applications; Learning Problems in OWL/DLs; Refinement Operators in OWL/DLs; Chapter 3. …”
Full text (MFA users only)

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

Full text (MFA users only)

Introduction to programming : learn to program in Java with data structures, algorithms, and logic by Samoylov, Nick

Full text (MFA users only)

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

Full text (MFA users only)

Building winning algorithmic trading systems : a trader's journey from data mining to Monte Carlo simulation to live trading by Davey, Kevin J., 1966-

Full text (MFA users only)

Algorithms, architectures and information systems security

Table of Contents: “…Theory of a Practical Delaunay Meshing Algorithm for a Large Class of Domains S.-W. Cheng, T.K. …”
Full text (MFA users only)

Network and discrete location : models, algorithms, and applications by Daskin, Mark S., 1952-

Full text (MFA users only)

Body sensor networking, design, and algorithms by Sanei, Saeid, Jarchi, Delaram, 1983-, Constantinides, A. G.

Full text (MFA users only)

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

Full text (MFA users only)

Learning JavaScript data structures and algorithms : understand and implement classic data structures and algorithms using JavaScript by Groner, Loiane

Full text (MFA users only)

Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms. by Dhope, Tanuja S.

Full text (MFA users only)

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…”
Full text (MFA users only)

Evolutionary algorithms for mobile ad hoc networks

Table of Contents: “…3 SURVEY ON OPTIMIZATION PROBLEMS FOR MOBILE AD HOC NETWORKS3.1 TAXONOMY OF THE OPTIMIZATION PROCESS; 3.2 STATE OF THE ART; 3.3 CONCLUSION; REFERENCES; 4 MOBILE NETWORKS SIMULATION; 4.1 SIGNAL PROPAGATION MODELING; 4.2 STATE OF THE ART OF NETWORK SIMULATORS; 4.3 MOBILITY SIMULATION; 4.4 CONCLUSION; REFERENCES; PART II: PROBLEMS OPTIMIZATION; 5 PROPOSED OPTIMIZATION FRAMEWORK; 5.1 ARCHITECTURE; 5.2 OPTIMIZATION ALGORITHMS; 5.3 SIMULATORS; 5.4 EXPERIMENTAL SETUP; 5.5 CONCLUSION; REFERENCES; 6 BROADCASTING PROTOCOL; 6.1 THE PROBLEM; 6.2 EXPERIMENTS; 6.3 ANALYSIS OF RESULTS; 6.4 CONCLUSION.…”
Full text (MFA users only)

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).…”
Full text (MFA users only)