Search Results - (((((((ant OR wants) OR semantic) OR wanted) OR cantor) OR anne) OR shared) OR hints) algorithms.

Three Views of Logic : Mathematics, Philosophy, and Computer Science. by Loveland, Donald W.

Table of Contents: “…Proof Theory; 1 Propositional Logic; 1.1 Propositional Logic Semantics; 1.2 Syntax: Deductive Logics; 1.3 The Resolution Formal Logic; 1.4 Handling Arbitrary Propositional Wffs; 2 Predicate Logic; 2.1 First-Order Semantics; 2.2 Resolution for the Predicate Calculus; 2.2.1 Substitution; 2.2.2 The Formal System for Predicate Logic; 2.2.3 Handling Arbitrary Predicate Wffs; 3 An Application: Linear Resolution and Prolog; 3.1 OSL-Resolution; 3.2 Horn Logic; 3.3 Input Resolution and Prolog; Appendix A: The Induction Principle.…”
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Big data in medical science and healthcare management : diagnosis, therapy, side effects

Table of Contents: “…Autopilot and "doctor algorithm"? -- 1. Intro big data for healthcare? / Peter Langkafel -- 2. …”
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Real-time database systems : architecture and techniques

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Gradience in grammar : generative perspectives

Table of Contents: “…Frisch and Adrienne Stearns -- Intermediate syntactic variants in a dialect : standard speech repertoire and relative acceptability / Leonie Cornips -- Gradedness and optionality in mature and developing grammars / Antonella Sorace -- Decomposing gradience : quantitative versus qualitative distinctions / Matthias Schlesewsky, Ina Bornkessel, and Brian McElree -- Gradient perception of intonation / Caroline Féry and Ruben Stoel -- Prototypicality judgements as inverted perception / Paul Boersma -- Modelling productivity with the gradual learning algorithm : the problem of accidentally exceptionless generalizations / Adam Albright and Bruce Hayes -- Gradedness as relative efficiency in the processing of syntax and semantics / John A. …”
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Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow. by Ravichandiran, Sudharsan

Table of Contents: “…Solving the taxi problem using Q learningSARSA; Solving the taxi problem using SARSA; The difference between Q learning and SARSA; Summary; Questions; Further reading; Chapter 6: Multi-Armed Bandit Problem; The MAB problem; The epsilon-greedy policy; The softmax exploration algorithm; The upper confidence bound algorithm; The Thompson sampling algorithm; Applications of MAB; Identifying the right advertisement banner using MAB; Contextual bandits; Summary; Questions; Further reading; Chapter 7: Deep Learning Fundamentals; Artificial neurons; ANNs; Input layer; Hidden layer; Output layer.…”
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Oracle Primavera P6 version 8 : project and portfolio management : a comprehensive guide to managing projects, resources, and portfolios using Primavera P6, through version 8.2 by Williams, Daniel L.

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Constraint Solving over Multi-valued Logics : Application to Digital Circuits.

Table of Contents: “…-- 3.2 Test Generation -- 3.3 TG Modelling Approaches and Algorithms.…”
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Cryptography 101 : From Theory to Practice. by Oppliger, Rolf

Table of Contents: “…12.2.3 Asymmetric Encryption-Based Key Distribution Protocol -- 12.3 KEY AGREEMENT -- 12.4 QUANTUM CRYPTOGRAPHY -- 12.4.1 Basic Principles -- 12.4.2 Quantum Key Exchange Protocol -- 12.4.3 Historical and Recent Developments -- 12.5 FINAL REMARKS -- References -- Chapter 13 Asymmetric Encryption -- 13.1 INTRODUCTION -- 13.2 PROBABILISTIC ENCRYPTION -- 13.2.1 Algorithms -- 13.2.2 Assessment -- 13.3 ASYMMETRIC ENCRYPTION SYSTEMS -- 13.3.1 RSA -- 13.3.2 Rabin -- 13.3.3 Elgamal -- 13.3.4 Cramer-Shoup -- 13.4 IDENTITY-BASED ENCRYPTION -- 13.5 FULLY HOMOMORPHIC ENCRYPTION -- 13.6 FINAL REMARKS -- References -- Chapter 14 Digital Signatures -- 14.1 INTRODUCTION -- 14.2 DIGITAL SIGNATURE SYSTEMS -- 14.2.1 RSA -- 14.2.2 PSS and PSS-R -- 14.2.3 Rabin -- 14.2.4 Elgamal -- 14.2.5 Schnorr -- 14.2.6 DSA -- 14.2.7 ECDSA -- 14.2.8 Cramer-Shoup -- 14.3 IDENTITY-BASED SIGNATURES -- 14.4 ONE-TIME SIGNATURES -- 14.5 VARIANTS -- 14.5.1 Blind Signatures -- 14.5.2 Undeniable Signatures -- 14.5.3 Fail-Stop Signatures -- 14.5.4 Group Signatures -- 14.6 FINAL REMARKS -- References -- Chapter 15 Zero-Knowledge Proofs of Knowledge -- 15.1 INTRODUCTION -- 15.2 ZERO-KNOWLEDGE AUTHENTICATION PROTOCOLS -- 15.2.1 Fiat-Shamir -- 15.2.2 Guillou-Quisquater -- 15.2.3 Schnorr -- 15.3 NONINTERACTIVE ZERO-KNOWLEDGE -- 15.4 FINAL REMARKS -- References -- Part IV CONCLUSIONS -- Chapter 16 Key Management -- 16.1 INTRODUCTION -- 16.1.1 Key Generation -- 16.1.2 Key Distribution -- 16.1.3 Key Storage -- 16.1.4 Key Destruction -- 16.2 SECRET SHARING -- 16.2.1 Shamir's System -- 16.2.2 Blakley's System -- 16.2.3 Verifiable Secret Sharing -- 16.2.4 Visual Cryptography -- 16.3 KEY RECOVERY -- 16.4 CERTIFICATE MANAGEMENT -- 16.4.1 Introduction -- 16.4.2 X.509 Certificates -- 16.4.3 OpenPGP Certificates -- 16.4.4 State of the Art -- 16.5 FINAL REMARKS -- References -- Chapter 17 Summary.…”
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Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications by Lantz, Brett

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HTML5 Multimedia Development Cookbook. by Cruse, Dale

Table of Contents: “…More flexible footer contentApplying the outline algorithm; Getting ready; How to do it ... ; How it works ... ; There's more ... ; Are you sure?…”
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Circuit analysis

Table of Contents: “…CIRCUIT ANALYSIS; ELECTRICAL ENGINEERINGDEVELOPMENTS; CONTENTS; PREFACE; ELEMENT STAMP ALGORITHM FOR MATRIXFORMULATION OF SYMBOLIC CIRCUITS; Abstract; 1. …”
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From text to political positions : text analysis across disciplines

Table of Contents: “…Conditional probabilities and associative framing ; Semantic network analysis.…”
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Challenges in information technology management

Table of Contents: “…Improved data mining algorithms for frequent patterns with composite items / Ke Wang, James N.K. …”
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Meeting security challenges through data analytics and decision support

Table of Contents: “…Counter Terrorism: Methodology and Applications; Arguing About Uncertain Heterogeneous Information for Threat Assessment; Intelligence Analysis: Needs and Solutions; Building Agile Human/Machine Teams with Controlled Natural Language; Military Usages of Speech and Language Technologies: A Review; Comparative Studies on Using Semantic Filtering for Open Relation Identification; Towards an Integration of Fusion of Information and Analytics Technologies (FIAT) to Improve Dependability and Security in Complex Systems; Data Fusion and Response Management.…”
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Fuzzy systems and data mining II : proceedings of FSDM 2016

Table of Contents: “…Adaptive Fuzzy Sliding-Mode Control of Robot and SimulationHesitant Bipolar Fuzzy Set and Its Application in Decision Making; Chance Constrained Twin Support Vector Machine for Uncertain Pattern Classification; Set-Theoretic Kripke-Style Semantics for Monoidal T-Norm (Based) Logics; Data Mining; Dynamic Itemset Mining Under Multiple Support Thresholds; Deep Learning with Large Scale Dataset for Credit Card Data Analysis; Probabilistic Frequent Itemset Mining Algorithm over Uncertain Databases with Sampling; Priority Guaranteed and Energy Efficient Routing in Data Center Networks.…”
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Smart buildings, smart communities and demand response

Table of Contents: “…Demand Response in Smart Zero Energy Buildings and Grids / Nikos Kampelis -- DR in Smart and Near-zero Energy Buildings: The Leaf Community / Nikos Kampelis, Konstantinos Gobakis, Vagias Vagias, Denia Kolokotsa, Laura Standardi, Daniela Isidori, Cristina Cristalli, Fabio Maria Montagnino, Filippo Paredes, Pietro Muratore, Luca Venezia, Marina Kyprianou Dracou, Alaric Montenon, Andri Pyrgou, Theoni Karlessi, Mattheos Santamouris -- Performance of Industrial and Residential Near-zero Energy Buildings / Nikos Kampelis, Konstantinos Gobakis, Vagias Vagias, Denia Kolokotsa, Laura Standardi, Daniela Isidori, Cristina Cristalli, Fabio Maria Montagnino, Filippo Paredes, Pietro Muratore, Luca Venezia, Marina Kyprianou Dracou, Alaric Montenon, Andri Pyrgou, Theoni Karlessi, Mattheos Santamouris -- HVAC Optimization Genetic Algorithm for Industrial Near-Zero Energy Building Demand Response / Nikos Kampelis, Nikolaos Sifakis, Denia Kolokotsa, Konstantinos Gobakis, Konstantinos Kalaitzakis, Daniela Isidori, Cristina Cristalli -- Smart Grid/Community Load Shifting GA Optimization Based on Day-ahead ANN Power Predictions / Nikos Kampelis, Elisavet Tsekeri, Denia Kolokotsa, Konstantinos Kalaitzakis, Daniela Isidori, Cristina Cristalli -- Conclusions and Recommendations.…”
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Database technology for life sciences and medicine

Table of Contents: “…The DIANOVA framework. 4.4. Algorithms for realizing DIANOVA. 4.5. Extensions of DIANOVA. 4.6. …”
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Numerical linear algebra with applications : using MATLAB by Ford, William H.

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Advanced Analytics with R and Tableau. by Stirrup, Jen

Table of Contents: “…; How to do Clustering in Tableau; Creating Clusters; Clustering example in Tableau; Creating a Tableau group from cluster results; Constraints on saving Clusters; Interpreting your results; How Clustering Works in Tableau; The clustering algorithm; Scaling; Clustering without using k-means; Hierarchical modeling; Statistics for Clustering; Describing Clusters -- Summary tab; Testing your Clustering.…”
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Fast sequential Monte Carlo methods for counting and optimization by Rubinstein, Reuven Y.

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