Search Results - (((((((kant OR wkant) OR semantic) OR went) OR cantor) OR anne) OR shared) OR hints) algorithms.

Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost by Mukherjee, Arindam

Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
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Computational models of argument : proceedings of COMMA 2014

Table of Contents: “…Properties of Random VAFs and Implications for Efficient AlgorithmsResolution-Based Grounded Semantics Revisited -- Decomposing Abstract Dialectical Frameworks -- A Principled Approach to the Implementation of Argumentation Models -- Combining Paraconsistent Logic with Argumentation -- Probabilistic Argument Graphs for Argumentation Lotteries -- Enthymeme Construction in Dialogues Using Shared Knowledge -- Strategies in Dialogues: A Game-Theoretic Approach -- Argumentation Logic -- Splitting Abstract Dialectical Frameworks…”
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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Communicating process architectures 2002. by World Occam And Transputer User Group. Technical Meeting (25th: 2002: University Of Reading, U. K.)

Table of Contents: “…Cover; Title page; Contents; Preface; Programme Committee; Papers; Semantics of prialt in Handel-C"! Acceptances, Behaviours and Infinite Activity in CSPP; HCSP: Imperative State and True Concurrency; Consolidating the Agreement Problem Protocol Verification Environment; On the Complexity of Buffer Allocation in Message Passing Systems; Java PastSet -- A Structured Distributed Shared Memory System; Synchronous Active Objects Introduce CSP's Primitives in Java; Configurable Collective Communication in LAM-MPI; Cache-Affinity Scheduling for Fine Grain Multithreading.…”
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Ivor Horton's beginning Visual C++ 2012 by Horton, Ivor

Table of Contents: “…Algorithms --…”
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Digital journalism, drones, and automation : the language and abstractions behind the news by Dowd, Cate

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Methods for Network Optimization and Parallel Derivative-free Optimization. by Olsson, Per-Magnus

Table of Contents: “…Intro -- Abstract -- Populärvetenskaplig sammanfattning -- Acknowledgements -- Thesis Introduction -- Contents -- Part I Contributions to Network Optimization -- 1 Introduction -- 2 Related Work -- 3 The Relay Positioning Problems -- 4 Environment Representation and Discretization -- 5 Relay Positioning Algorithms for Single Target Problems -- 6 Relay Positioning for Multiple Targets -- 7 Implementation and Experimental Results -- 8 Discussion -- Bibliography -- Part II Contributions to Derivative-free Optimization -- 9 Introduction -- 10 Setting And Problem Description -- 11 Direct Search Algorithms -- 12 Model Building Algorithms -- 13 Existing Model Building Algorithms -- 14 Radial Basis Functions -- 15 Parallelism in Algorithms for Derivative-Free Optimization -- 16 Information Sharing -- 17 Control of Optimization Algorithms -- 18 Implementation Details -- 19 Testing on Synthetic Test Cases -- 20 Testing On Industrial Test Cases -- 21 Future Work -- 22 Conclusions -- A Terms -- Bibliography.…”
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Navigation signal processing for GNSS software receivers by Pany, Thomas

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Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios, 1951-

Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
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Autonomous mobile robots and multi-robot systems : motion-planning, communication, and swarming

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Modeling Reality : How Computers Mirror Life. by Białynicki-Birula, Iwo

Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
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Advances in intelligent IT : active media technology 2006

Table of Contents: “…Title page; Preface; Organization; Contents; Keynotes; Active Media Technologies (AMT) from the Standpoint of the Wisdom Web; Anytime Learning and Classification for Online Applications; Domain-Driven Data Mining: Methodologies and Applications; Regular Papers; Web Service Request Transformatter; A Head-Tracker Based on the Lucas-Kanade Optical Flow Algorithm; A Fair Peer Selection Algorithm for an Ecommerce-Oriented Distributed Recommender System; Intelligent Decision Making with the Semantic Web; Relevence Assessment of Topic Ontology; Information Extraction from a Whole Web Site.…”
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Challenges and opportunities of HealthGrids : proceedings of Healthgrid 2006

Table of Contents: “…Advancing of Russian ChemBioGrid by Bringing Data Management Tools into Collaborative EnvironmentGPS@ Bioinformatics Portal: From Network to EGEE Grid; Blast2GO Goes Grid: Developing a Grid-Enabled Prototype for Functional Genomics Analysis; Bioprofiling over Grid for eHealthcare; SARS Grid-An AG-Based Disease Management and Collaborative Platform; Knowledge Discovery on HealthGrids; A Secure Semantic Interoperability Infrastructure for Inter-Enterprise Sharing of Electronic Healthcare Records.…”
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Scientific computing with multicore and accelerators

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Analytical modeling of wireless communication systems by Chiasserini, C. F. (Carla-Fabiani), Gribaudo, Marco, 1972-, Manini, Daniele

Table of Contents: “…Safety Message Broadcasting -- Modeling Information Sharing -- Cellular Networks. Multi-RAT Algorithms.…”
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What intelligence tests miss : the psychology of rational thought by Stanovich, Keith E., 1950-

Table of Contents: “…Inside George W. Bush's mind : hints at what IQ tests miss -- Dysrationalia : separating rationality and intelligence -- The reflective mind, the algorithmic mind, and the autonomous mind -- Cutting intelligence down to size -- Why intelligent people doing foolish things is no surprise -- The cognitive miser : ways to avoid thinking -- Framing and the cognitive miser -- Myside processing : heads I win, tails I win too! …”
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Intelligent Technologies : From Theory to Applications - The New Trends in Computational Intelligence. by Kvasnicka, V.

Table of Contents: “…Neural Networks; Superconvergence Concept in Machine Learning; Application of the Parallel Population Learning Algorithm to Training Feed-forward ANN; Markovian Architectural Bias of Recurrent Neural Networks; SOFM Training Speedup; Generalized Forecasting Sigma-Pi Neural Network; Human Centered Intelligent Robots Using "Ontological Neural Network"; Trajectory Bounds of Solutions of Delayed Cellular Neural Networks Differential Systems; From Plain to Modular Topology: Automatic Modularization of Structured ANNs.…”
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Handbook of Mathematical Induction. by Gunderson, David S.

Table of Contents: “…Chapter 14: Logic and languageChapter 15: Graphs; Chapter 16: Recursion and algorithms; Chapter 17: Games and recreations; Chapter 18: Relations and functions; Chapter 19: Linear and abstract algebra; Chapter 20: Geometry; Chapter 21: Ramsey theory; Chapter 22: Probability and statistics; Part III: Solutions and hints to exercises; Chapter 23: Solutions: Foundations; Chapter 24: Solutions: Inductive techniques applied to the infinite; Chapter 25: Solutions: Paradoxes and sophisms; Chapter 26: Solutions: Empirical induction; Chapter 27: Solutions: Identities.…”
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Artificial intelligence : approaches, tools, and applications

Table of Contents: “…EVOLUTIONARY COMPUTING ; 2.1. Genetic Algorithms ; 2.2. Mechanism of a Genetic Algorithm ; 3. …”
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Cybernetic intelligent systems

Table of Contents: “…Cover ; Editorial advisory board ; Editorial ; Guest editorial ; HDR imaging for feature tracking in challenging visibility scenes ; A new classification strategy for human activity recognition using cost sensitive support vector machines for imbalanced data ; Coarticulation and speech synchronization in MPEG-4 based facial animation ; Semantic Category theory and Semantic Intertwine: the anathema of mathematics ; Tracking progress of African Peer Review Mechanism (APRM) using fuzzy comprehensive evaluation method.…”
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