Search Results - (((((((want OR wanting) OR art) OR halted) OR cantor) OR anne) OR cartsr) OR hints) algorithms.

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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The NURBS Book by Piegl, Les

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MATLAB for Machine Learning. by Ciaburro, Giuseppe

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Graph drawing and applications for software and knowledge engineers by Sugiyama, Kozo, 1945-

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Cryptography 101 : From Theory to Practice. by Oppliger, Rolf

Table of Contents: “…Intro -- Cryptography 101: From Theory to Practice -- Contents -- Foreword -- Preface -- References -- Acknowledgments -- Chapter 1 Introduction -- 1.1 CRYPTOLOGY -- 1.2 CRYPTOGRAPHIC SYSTEMS -- 1.2.1 Classes of Cryptographic Systems -- 1.2.2 Secure Cryptographic Systems -- 1.3 HISTORICAL BACKGROUND INFORMATION -- 1.4 OUTLINE OF THE BOOK -- References -- Chapter 2 Cryptographic Systems -- 2.1 UNKEYED CRYPTOSYSTEMS -- 2.1.1 Random Generators -- 2.1.2 Random Functions -- 2.1.3 One-Way Functions -- 2.1.4 Cryptographic Hash Functions -- 2.2 SECRET KEY CRYPTOSYSTEMS -- 2.2.1 Pseudorandom Generators -- 2.2.2 Pseudorandom Functions -- 2.2.3 Symmetric Encryption -- 2.2.4 Message Authentication -- 2.2.5 Authenticated Encryption -- 2.3 PUBLIC KEY CRYPTOSYSTEMS -- 2.3.1 Key Establishment -- 2.3.2 Asymmetric Encryption Systems -- 2.4 FINAL REMARKS -- References -- Part I UNKEYEDC RYPTOSYSTEMS -- Chapter 3 Random Generators -- 3.1 INTRODUCTION -- 3.2 REALIZATIONS AND IMPLEMENTATIONS -- 3.2.1 Hardware-Based Random Generators -- 3.2.2 Software-Based Random Generators -- 3.2.3 Deskewing Techniques -- 3.3 STATISTICAL RANDOMNESS TESTING -- References -- Chapter 4 Random Functions -- 4.1 INTRODUCTION -- 4.2 IMPLEMENTATION -- 4.3 FINAL REMARKS -- Chapter 5 One-Way Functions -- 5.1 INTRODUCTION -- 5.2 CANDIDATE ONE-WAY FUNCTIONS -- 5.2.1 Discrete Exponentiation Function -- 5.2.2 RSA Function -- 5.2.3 Modular Square Function -- 5.3 INTEGER FACTORIZATION ALGORITHMS -- 5.3.1 Special-Purpose Algorithms -- 5.3.2 General-Purpose Algorithms -- 5.3.3 State of the Art -- 5.4 ALGORITHMS FOR COMPUTING DISCRETE LOGARITHMS -- 5.4.1 Generic Algorithms -- 5.4.2 Nongeneric (Special-Purpose) Algorithms -- 5.4.3 State of the Art -- 5.5 ELLIPTIC CURVE CRYPTOGRAPHY -- 5.6 FINAL REMARKS -- References -- Chapter 6 Cryptographic Hash Functions -- 6.1 INTRODUCTION.…”
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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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The bitcoin big bang : how alternative currencies are about to change the world by Kelly, Brian, 1971-

Table of Contents: “…; What Is Cryptography?; Still Want to Be a Miner?; Do We Need Another Bitcoin?; 7 Nautiluscoin-0 to 1 Million in 60 Days; Creating the Coin; Did It Work?…”
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Mobile opportunistic networks : architectures, protocols and applications

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Advanced reliability modeling II : reliability testing and improvement : proceedings of the 2nd Asian International Workshop (AIWARM 2006), Busan, Korea, 24-26 August 2006

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Co-Clustering. by Govaert, G?rard

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Big Data and HPC. by Grandinetti, L.

Table of Contents: “…Analysis and Design of IoT Based Physical Location Monitoring SystemAutonomous Task Scheduling for Fast Big Data Processing; Adaptive Resource Management for Distributed Data Analytics; HPC Challenges; High-Performance Massive Subgraph Counting Using Pipelined Adaptive-Group Communication; Final Parallel and Distributed Computing Assignment for Master Students: Description of the Properties and Parallel Structure of Algorithms; Parallel Motion Estimation Based on GPU and Combined GPU-CPU; GPU-Based Iterative Hill Climbing Algorithm to Solve Symmetric Traveling Salesman Problem.…”
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Semi-supervised learning

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Kernels for structured data by Gärtner, Thomas

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Computational Continuum Mechanics. by Shabana, Ahmed A.

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Electromagnetic well logging : models for MWD/LWD interpretation and tool design by Chin, Wilson C.

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Springer handbook of global navigation satellite systems

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Large Aperture Array Radar Systems for Automotive Applications. by Schwartau, Fabian

Table of Contents: “…Optimization Algorithm -- Final Design -- Array Analysis -- Link-Budget -- Signal Processing Flow -- Summary -- 3.1 State of the Art -- 3.2 Requirements -- 3.3 Array Design -- 3.4 Array Analysis -- 3.5 Link-Budget -- 3.6 Signal Processing Flow -- 3.7 Summary -- Synchronization Demonstrator -- Hardware and Concept -- Radar Chips -- Module Hardware -- Module Synchronization -- Antenna Elements and Array -- Calibration -- System Parameters, Software and Signal Processing -- Simulations, Measurements and Results -- Summary -- 4.1 Hardware and Concept -- 4.2 Calibration…”
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Scala for Machine Learning - Second Edition. by Nicolas, Patrick R.

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Algebraic Multigrid for the Multi-Ion Transport and Reaction Model - a Physics-Aware Approach by Thum, Peter

Table of Contents: “…4.5 Sorting Algorithms4.6 Scalar Example; 4.7 Reordering Framework for the MITReM; 5 The Heuristic Peclet Number; 5.1 Heuristic Peclet Number for Scalar Equations; 5.2 Heuristic Peclet Number for Systems of PDEs; 6 A Physics-Aware Point-Based AMG Approach (PAMG) for the Migration-Diffusion System; 6.1 The Migration-Diffusion System; 6.2 State-of-the-Art PAMG Approaches; 6.3 The Physics-Aware Primary Matrix; 6.4 PAMG for a Locally Violated Peclet Condition; 6.5 The Final Physics-Aware PAMG Approach; 7 A Physics-Aware PAMG Approach for the MITReM; 7.1 The MITReM System…”
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Oracle SOA Suite 11g Performance Cookbook. by Brasier, Matthew

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