Search Results - (((((((want OR canton) OR mantis) OR wind) OR cantor) OR anne) OR share) OR hints) algorithms.

Hands-On Blockchain with Hyperledger : Building Decentralized Applications with Hyperledger Fabric and Composer. by Baset, Salman

Table of Contents: “…Decentralization with systemic governanceEnterprise support; Use case-driven pluggability choices; Shared ledger technology; Consensus; Crypto algorithms and encryption technology; Use case-driven pluggable choices; Enterprise integration and designing for extensibility; Other considerations; Consensus, ACID property, and CAP; CAP; ACID; Attestation -- SSCs are signed and encrypted; Use of HSMs; Summary; Chapter 2: Exploring Hyperledger Fabric; Building on the foundations of open computing; Fundamentals of the Hyperledger project; The Linux Foundation ; Hyperledger.…”
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Creating wicked students : designing courses for a complex world by Hanstedt, Paul, 1965-

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Cognitive Electronic Warfare : An Artificial Intelligence Approach. by Haigh, Karen

Table of Contents: “…-- 1.5 Reader's Guide -- 1.6 Conclusion -- References -- 2 Objective Function -- 2.1 Observables That Describe the Environment -- 2.1.1 Clustering Environments -- 2.2 Control Parameters to Change Behavior -- 2.3 Metrics to Evaluate Performance -- 2.4 Creating a Utility Function -- 2.5 Utility Function Design Considerations -- 2.6 Conclusion -- References -- 3 ML Primer -- 3.1 Common ML Algorithms -- 3.1.1 SVMs -- 3.1.2 ANNs -- 3.2 Ensemble Methods -- 3.3 Hybrid ML -- 3.4 Open-Set Classification -- 3.5 Generalization and Meta-learning -- 3.6 Algorithmic Trade-Offs -- 3.7 Conclusion -- References -- 4 Electronic Support -- 4.1 Emitter Classification and Characterization -- 4.1.1 Feature Engineering and Behavior Characterization -- 4.1.2 Waveform Classification -- 4.1.3 SEI -- 4.2 Performance Estimation -- 4.3 Multi-Intelligence Data Fusion -- 4.3.1 Data Fusion Approaches -- 4.3.2 Example: 5G Multi-INT Data Fusion for Localization -- 4.3.3 Distributed-Data Fusion -- 4.4 Anomaly Detection -- 4.5 Causal Relationships -- 4.6 Intent Recognition -- 4.6.1 Automatic Target Recognition and Tracking -- 4.7 Conclusion -- References -- 5 EP and EA -- 5.1 Optimization -- 5.1.1 Multi-Objective Optimization -- 5.1.2 Searching Through the Performance Landscape -- 5.1.3 Optimization Metalearning -- 5.2 Scheduling -- 5.3 Anytime Algorithms -- 5.4 Distributed Optimization -- 5.5 Conclusion.…”
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Pulmonary arterial hypertension : diagnosis and evidence-based treatment

Table of Contents: “…Combination therapy in pulmonary arterial hypertension / Anne Keogh and Marius Hoeper -- Interventional and surgical modalities of treatment for pulmonary arterial hypertension / Julio Sandoval and Ramona Doyle -- End points and clinical trial design in pulmonary arterial hypertension : clinical and regulatory perspectives / Andrew J. …”
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Machine Learning with Swift : Artificial Intelligence for iOS. by Sosnovshchenko, Oleksandr

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Code : Collaborative Ownership and the Digital Economy. by Ghosh, Rishab Aiyer

Table of Contents: “…Oral Traditions, Indigenous Rights, and Valuable Old Knowledge -- 7 From Keeping "Nature's Secrets" to the Institutionalization of "Open Science" -- 8 Benefit Sharing: Experiments in Governance -- 9 Trust among the Algorithms: Ownership, Identity, and the Collaborative Stewardship of Information -- 10 Cooking-Pot Markets and Balanced Value Flows -- 11 Coase's Penguin, or, Linux and the Nature of the Firm -- 12 Paying for Public Goods -- 13 Fencing Off Ideas: Enclosure and the Disappearance of the Public Domain -- 14 A Renaissance of the Commons: How the New Sciences and Internet are Framing a New Global Identity and Order -- 15 Positive Intellectual Rights and Information Exchanges -- 16 Copyright and Globalization in the Age of Computer Networks -- Contributors -- Index.…”
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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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Applied mechatronics and android robotics : selected, peer reviewed papers from the International Conference on Applied Mechatronics and Android Robotics (ICAMAR 2013), July 13-14,...

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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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Parallel computing : technology trends

Table of Contents: “…Feedback-Driven Performance and Precision Tuning for Automatic Fixed Point Exploitation -- Parallel Programming -- A GPU-CUDA Framework for Solving a Two-Dimensional Inverse Anomalous Diffusion Problem -- Parallelization Strategies for GPU-Based Ant Colony Optimization Applied to TSP -- DBCSR: A Blocked Sparse Tensor Algebra Library -- Acceleration of Hydro Poro-Elastic Damage Simulation in a Shared-Memory Environment -- BERTHA and PyBERTHA: State of the Art for Full Four-Component Dirac-Kohn-Sham Calculations -- Prediction-Based Partitions Evaluation Algorithm for Resource Allocation…”
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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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Visible Business : Uncover the Blindspots and Engage the World's Female Economy. by Brideson, RJ

Table of Contents: “…Blind Spots; Contents; Foreword; About the Author; Acknowledgements; To my community; To my village; Preface; Introduction; Chapter 1 From history to herstory; The birth of business marketing; Things have changed -- or have they?; Women want more; The wo-man algorithm; Become conscious of the bias; From reject to results; Chapter 2 Are you blind?…”
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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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Architecture-aware optimization strategies in real-time image processing by Li, Chao, Balla-Arabe, Souleymane, Yang, Fan

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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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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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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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Machine Learning for Asset Management New Developments and Financial Applications

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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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