Search Results - (((((((ant OR ckanton) OR semantic) OR wind) OR cantor) OR anne) OR share) OR hints) algorithms.

Pattern Recognition in Computational Molecular Biology : Techniques and Approaches by Elloumi, Mourad, Iliopoulos, Costas, Wang, Jason T. L., Zomaya, Albert Y.

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Verification of communication protocols in web services : model-checking service compositions by Mukherjee, Anshuman

Table of Contents: “…8.2 Overview of the Problem and Solution8.3 Related Work; 8.4 Colored Petri Net Semantics for BPEL; 8.4.1 Component A; 8.4.2 Component B; 8.4.3 Object Model for BPEL Activities; 8.4.4 XML Templates; 8.4.5 Algorithm for Cloning Templates; 8.5 Results; 8.6 Discussion; 8.7 Summary; References; 9 CONCLUSIONS AND OUTLOOK; 9.1 Results; 9.2 Discussion; 9.3 What Could Be Improved?…”
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Mechanisms and games for dynamic spectrum allocation

Table of Contents: “…7.3.10 Other equilibrium concepts -- 7.4 Learning equilibria -- 7.4.1 Learning Nash equilibria -- 7.4.2 Learning epsilon-equilibrium -- 7.4.3 Learning coarse correlated equilibrium -- 7.4.4 Learning satisfaction equilibrium -- 7.4.5 Discussion -- 7.5 Conclusion -- References -- II Cognitive radio and sharing of unlicensed spectrum -- 8 Cooperation in cognitiveradio networks: from accessto monitoring -- 8.1 Introduction -- 8.1.1 Cooperation in cognitive radio: mutual benefits and costs -- 8.2 An overview of coalitional game theory -- 8.3 Cooperative spectrum exploration and exploitation -- 8.3.1 Motivation -- 8.3.2 Basic problem -- 8.3.3 Joint sensing and access as a cooperative game -- 8.3.4 Coalition formation algorithm for joint sensing and access -- 8.3.5 Numerical results -- 8.4 Cooperative primary user activity monitoring -- 8.4.1 Motivation -- 8.4.2 Primary user activity monitoring: basic model -- 8.4.3 Cooperative primary user monitoring -- 8.4.4 Numerical results -- 8.5 Summary -- Acknowledgements -- Copyright notice -- References -- 9 Cooperative cognitive radios with diffusion networks -- 9.1 Introduction -- 9.2 Preliminaries -- 9.2.1 Basic tools in convex and matrix analysis -- 9.2.2 Graphs -- 9.3 Distributed spectrum sensing -- 9.4 Iterative consensus-based approaches -- 9.4.1 Average consensus algorithms -- 9.4.2 Acceleration techniques for iterative consensus algorithms -- 9.4.3 Empirical evaluation -- 9.5 Consensus techniques based on CoMAC -- 9.6 Adaptive distributed spectrum sensing based on adaptive subgradient techniques -- 9.6.1 Distributed detection with adaptive filters -- 9.6.2 Set-theoretic adaptive filters for distributed detection -- 9.6.3 Empirical evaluation -- 9.7 Channel probing -- 9.7.1 Introduction -- 9.7.2 Admissibility problem -- 9.7.3 Power and admission control algorithms.…”
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There's Something about Gödel : The Complete Guide to the Incompleteness Theorem. by Berto, Francesco

Table of Contents: “…. -- 6 ... and the unsatisfied logicists, Frege and Russell -- 7 Bits of set theory -- 8 The Abstraction Principle -- 9 Bytes of set theory -- 10 Properties, relations, functions, that is, sets again -- 11 Calculating, computing, enumerating, that is, the notion of algorithm…”
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Randomness through computation : some answers, more questions

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Calculating the Secrets of Life : Contributions of the Mathematical Sciences to Molecular Biology. by Lander, Eric S.

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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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R High Performance Programming. by Lim, Aloysius

Table of Contents: “…Data parallelism versus task parallelismImplementing data parallel algorithms; Implementing task parallel algorithms; Running the same task on workers in a cluster; Running different tasks on workers in a cluster; Executing tasks in parallel on a cluster of computers; Shared memory versus distributed memory parallelism; Optimizing parallel performance; Summary; Chapter 9: Offloading Data Processing to Database Systems; Extracting data into R versus processing data in a database; Preprocessing data in a relational database using SQL; Converting R expressions into SQL; Using dplyr…”
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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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Mathematics and Multi-Ethnic Students : Exemplary Practices. by Germain- Mc Carthy, Yvelyne

Table of Contents: “…LYNNE GODFREY: AFRICAN AMERICANS AND THE ALGEBRA PROJECT; Engaging Students; Warm-Up; Group Work; The Winding Game; Discussion between Colleagues; Commentary; Unit Overview: The Chinese Zodiac and the Division Algorithm; 5. …”
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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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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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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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