Search Results - (((((((ken OR canton) OR semantic) OR wind) OR cantor) OR anne) OR plane) OR hints) algorithms.

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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Random Iterative Models by Duflo, Marie

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

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Handbook of mathematical formulas by Bartsch, Hans-Jochen

Table of Contents: “…Analytical geometry of the plane; 4.2. Analytical geometry of space; Chapter 5. …”
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Network and discrete location : models, algorithms, and applications by Daskin, Mark S., 1952-

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Improved Indirect Power Control (IDPC) of Wind Energy Conversion Systems (WECS) by Amrane, Fayssal, Chaiba, Azeddine

Table of Contents: “…Robustness Tests7 for Mode 1, Mode 2 Mode 3 -- A-Mode 1 (Novel IDPC based on T1-FLC, T2-FLC NFC): -- B-Mode 2 (Novel IDPC based on T1-FLC, T2-FLC NFC): -- C-Mode 3 (Novel IDPC based on T1-FLC, T2-FLC NFC): -- 7. WIND-SYSTEM PERFORMANCES RECAPITULATION UNDER SIX (06) PROPOSED IDPC ALGORITHMS -- CONCLUSION -- NOTES -- REFERENCES -- General Conclusion -- 5.1. …”
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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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Coherent Doppler Wind Lidars in a Turbulent Atmosphere. by Banakh, V. A. (Viktor Arsentʹevich)

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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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Randomization, Relaxation, and Complexity in Polynomial Equation Solving. by Gurvits, Leonid

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Fundamentals of grid computing : theory, algorithms and technologies

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Romance syntax, semantics and L2 acquisition : selected papers from the 30th Linguistic Symposium on Romance Languages : Gainesville, Florida, February 2000

Table of Contents: “…ROMANCE SYNTAX, SEMANTICS AND L2 ACQUISITION -- Editorial page -- Title page -- Copyright page -- Acknowledgements -- Table of contents -- CONTRIBUTORS -- Dedication -- ROMANCE SYNTAX, SEMANTICS, AND L2 ACQUISITION -- 0. …”
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What Is Thought? by Baum, Eric B., 1957-

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Condition Monitoring with Vibration Signals : Compressive Sampling and Learning Algorithms for Rotating Machines. by Nandi, Asoke K.

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Supersonic Business Jets in Preliminary Aircraft Design. by Schuermann, Martin

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All Source Positioning, Navigation and Timing by Li, Rongsheng, Ph. D.

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Entity information life cycle for big data : master data management and information integration by Talburt, John R., Zhou, Yinle, 1986-

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