Search Results - (((((((ant OR want) OR semantic) OR went) OR cantor) OR anne) OR share) OR hints) algorithms.

  1. 181

    Risk management technology in financial services : risk control, stress testing, models, and IT systems and structures by Chorafas, Dimitris N.

    Published 2007
    Table of Contents: “…-- Chapter 3 Complxity of risk control with derivatives -- Chapter 4 Intergrating risk management through an enterprise architecure -- Chapter 5 Case studies on big product problems that went unattended -- Part 2 Risk control methodology and advanced models -- Chapter 6 A methodology for risk management -- Chapter 7 The contribution of models to experimentation -- Chapter 8 Simulation -- Chapter 9 Using knowledge engineering for risk control -- Chapter 10 Optimization through genetic algorithms -- Chapter 11 Testing, backtesting, post-mortems and experimental methodology -- Part 3 Increasing the effectiveness of information systems support -- Chapter 12 Adding value to risk control through IT and organization -- Chapter 13 Technology for time management, high frequency financial data and high impact events -- Chapter 14 Project management for IT and risk control -- Chapter 15 Implementing design reviews -- Chapter 16 Quality, reliability and availability -- Chapter 17 Being in charge of IT costs -- Index.…”
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  2. 182

    Rediscovering mathematics : you do the math by Simonson, Shai

    Published 2011
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  3. 183

    Advanced Methods and Technologies for Agent and Multi-Agent Systems. by Edited by

    Published 2013
    Table of Contents: “…""Role and Member Selection in Team Formation Using Resource Estimation""""Incorporating Explicit Coordination Mechanisms by Agents to Obtain Green Waves""; ""Communication Leading to Coalition Nash Equilibrium I""; ""Agent-Based Optimization""; ""An Agent-Based Cooperative Population Learning Algorithm for Vehicle Routing Problem with Time Windows""; ""Mobile Agent-based Dynamic Resource Allocation Method for Query Optimization in Data Grid Systems""; ""Memetic Multi-Agent Computing in Difficult Continuous Optimisation""; ""Web Services and Semantic Web""…”
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  4. 184

    Visual Data Mining : The VisMiner Approach. by Anderson, Russell K.

    Published 2012
    Table of Contents: “…Regression Analysis -- The Regression Model -- Correlation and Causation -- Algorithms for Regression Analysis -- Assessing Regression Model Performance -- Model Validity -- Looking Beyond R2 -- Polynomial Regression -- Artificial Neural Networks for Regression Analysis -- Dataset Preparation -- Tutorial -- A Regression Model for Home Appraisal -- Modeling with the Right Set of Observations -- Exercise 6.1 -- ANN Modeling -- The Advantage of ANN Regression -- Top-Down Attribute Selection -- Issues in Model Interpretation -- Model Validation -- Model Application -- Summary…”
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  5. 185

    DSP with Python Programming. by Charbit, Maurice

    Published 2017
    Table of Contents: “…Gaussian linear case: Kalman algorithm; 3.5. Discrete finite Markov case; 4 Monte-Carlo Methods; 4.1. …”
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  6. 186

    Artificial intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques. by Deshpande, Anand

    Published 2018
    Table of Contents: “…Snowball stemming -- Lancaster stemming -- Lovins stemming -- Dawson stemming -- Lemmatization -- N-grams -- Feature extraction -- One hot encoding -- TF-IDF -- CountVectorizer -- Word2Vec -- CBOW -- Skip-Gram model -- Applying NLP techniques -- Text classification -- Introduction to Naive Bayes' algorithm -- Random Forest -- Naive Bayes' text classification code example -- Implementing sentiment analysis -- Frequently asked questions -- Summary -- Chapter 7: Fuzzy Systems -- Fuzzy logic fundamentals -- Fuzzy sets and membership functions -- Attributes and notations of crisp sets -- Operations on crisp sets -- Properties of crisp sets -- Fuzzification -- Defuzzification -- Defuzzification methods -- Fuzzy inference -- ANFIS network -- Adaptive network -- ANFIS architecture and hybrid learning algorithm -- Fuzzy C-means clustering -- NEFCLASS -- Frequently asked questions -- Summary -- Chapter 8: Genetic Programming -- Genetic algorithms structure -- KEEL framework -- Encog machine learning framework -- Encog development environment setup -- Encog API structure -- Introduction to the Weka framework -- Weka Explorer features -- Preprocess -- Classify -- Attribute search with genetic algorithms in Weka -- Frequently asked questions -- Summary -- Chapter 9: Swarm Intelligence -- Swarm intelligence -- Self-organization -- Stigmergy -- Division of labor -- Advantages of collective intelligent systems -- Design principles for developing SI systems -- The particle swarm optimization model -- PSO implementation considerations -- Ant colony optimization model -- MASON Library -- MASON Layered Architecture -- Opt4J library -- Applications in big data analytics -- Handling dynamical data -- Multi-objective optimization -- Frequently asked questions -- Summary -- Chapter 10: Reinforcement Learning -- Reinforcement learning algorithms concept.…”
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  7. 187
  8. 188

    Focus on artificial neural networks

    Published 2011
    Table of Contents: “…ARTIFICIAL NEURAL NETWORKS (ANNS) -- 3. MICROEMULSIONS -- 4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS -- 4.1. …”
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  9. 189

    Implementing cryptography using Python by Bray, Shannon, 1972-

    Published 2020
    Table of Contents: “…Chapter 2 Cryptographic Protocols and Perfect Secrecy -- The Study of Cryptology -- Understanding Cryptography -- Cryptography's Famous Family: Alice and Bob -- Diffie-Hellman -- Data Origin Authentication -- Entity Authentication -- Symmetric Algorithms -- Asymmetric Algorithms -- The Needham-Schroeder Protocols -- The Otway-Rees Protocol -- Kerberos -- Multiple-Domain Kerberos -- X.509 -- Formal Validation of Cryptographic Protocols -- Configuring Your First Cryptographic Library -- Understanding Cryptanalysis -- Brute-Force Attacks -- Side-Channel Attacks -- Social Engineering…”
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  10. 190

    Mastering D3.js. by Castillo, Pablo Navarro

    Published 2014
    Table of Contents: “…Updating the datasetFixing the enter and exit transitions; Using the barcode chart; Creating a layout algorithm; The radial layout; Computing the angles; Using the layout; Summary; Chapter 3: Creating Visualizations without SVG; SVG support in the browser market; Visualizations without SVG; Loading and sorting the data; The force layout method; Setting the color and size; Creating a legend; Polyfilling; Feature detection; The canvg example; Using canvas and D3; Creating figures with canvas; Creating shapes; Integrating canvas and D3; Summary; Chapter 4: Creating a Color Picker with D3.…”
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  11. 191

    Metaheuristics for vehicle routing problems. by Labadie, Nacima

    Published 2015
    Table of Contents: “…Memetic algorithm; 4.1.3. Memetic algorithm with population management; 4.1.4. …”
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  12. 192

    Industrial control systems

    Published 2011
    Table of Contents: “…EXTRACTIVE FERMENTATION PROCESS FOR BIOETHANOL PRODUCTION ; 3. PLANT MODEL BASED ON ANN ; 3.1. ANN Configurations.…”
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  13. 193

    Regression Analysis with Python. by Massaron, Luca, Boschetti, Alberto

    Published 2016
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  14. 194
  15. 195

    Computational models of argument : Proceedings of COMMA 2012

    Published 2012
    Table of Contents: “…Simari -- Automated Deployment of Argumentation Protocols / Michael Rovatsos -- On Preferred Extension Enumeration in Abstract Argumentation / Katie Atkinson -- Towards Experimental Algorithms for Abstract Argumentation / Katie Atkinson.…”
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  16. 196

    Automata and Computability. by Kozen, Dexter, 1951-

    Published 1997
    Table of Contents: “…Miscellaneous Exercises Turing Machines and Effective ComputabilityHints for Selected Miscellaneous Exercises; Solutions to Selected Miscellaneous Exercises; References; Notation and Abbreviations; Index.…”
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  17. 197

    QoS and Energy Management in Cognitive Radio Network : Case Study Approach. by Mishra, Vishram

    Published 2016
    Table of Contents: “…1.6.1 Channel Selection in CR Based Infrastructure Network1.6.2 Channel Selection in CR Based Ad-hoc Network; 1.7 MAC Protocols for Cognitive Radio Networks; 1.7.1 Random Access Based MAC Scheme; 1.7.2 Time-Slotted Based MAC Scheme; 1.8 Self-coexistence in Cognitive Radio Networks; 1.8.1 Resource Relocation Based Self-coexistence; 1.8.2 Resource Sharing Based Self-coexistence; 1.9 Discussion; References; 2 Cognitive Radio Network- A Review; 2.1 Spectrum Management; 2.1.1 Ant Colony Optimization Based Spectrum Management; 2.1.2 Non-linear Optimization Based Spectrum Management.…”
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  18. 198

    Mathematical morphology and its applications to image and signal processing

    Published 2000
    Table of Contents: “…Geodesic Set Definition in Case of Empty Intersection -- The Morphological-Affine Object Deformation -- Affine Invariant Mathematical Morphology Applied to a Generic Shape Recognition Algorithm -- Filtering -- Folding Induced Self-Dual Filters -- Flexible Linear Openings and Closings -- Some Applications of Aperture Filters -- GA Optimisation of Multidimensional Grey-Scale Soft Morphological Filters with Applications in Archive Film Restoration -- Connectivity and Connected Operators -- New Insight on Digital Topology -- Approximate Connectivity and Mathematical Morphology -- Multiresolution Connectivity: An Axiomatic Approach -- Connected Operators Based on Region-Tree Pruning -- Segmentation -- Image Segmentation Based on the Derivative of the Morphological Profile -- Flooding and Segmentation -- A Morphological Multi-Scale Gradient for Color Image Segmentation -- Automatic Watershed Segmentation of Color Images -- Motion Segmentation using Seeded Region Growing -- A Segmentation Pyramid for the Interactive Segmentation of 3-D Images and Video Sequences -- Partition Lattice Operators for Extraction of Semantic Video Objects -- Texture Analysis -- Morphological Granulometric Deconstruction -- Surface Texture Classification from Morphological Transformations -- Content Dependent Image Sampling using Mathematical Morphology: Application to Mipmapping -- Multiresolution Techniques and Scale-Spaces -- Morphological Pyramids and Wavelets Based on the Quincunx Lattice -- Morphological Scale-Space Operators: An Algebraic Framework -- An Idempotent Scale-Space Approach for Morphological Segmentation -- Algorithms -- Efficient Dilation, Erosion, Opening and Closing Algorithms -- Fast Morphological Attribute Operations using Tarjan's Union-Find Algorithm -- A Change Detector Based on Level Sets -- A General Algorithm for Computing Distance Transforms in Linear Time -- The Ordered Queue and the Optimality of the Watershed Approaches -- Discrete 3D Wave Propagation for Computing Morphological Operations from Surface Patches and Unorganized Points -- Applications -- Two-Stage Lossy/Lossless Compression of Grayscale Document Images -- Boosting OCR Classifier by Optimal Edge Noise Filtering -- Morphological Bank Check Logo Segmentation with Few a Priori Knowledge -- Morphological Pseudo Convex Hull to Correct Handwriting Baseline Skew -- Morphological Segmentation of Text and Figures in Renaissance Books (XVI Century) -- Application of Mathematical Morphology and Markov Random Field Theory to the Automatic Extraction of Linear Features in Airborne Images -- Testing Some Morphological Approaches to Face Localization -- Quantitative Description of Telecommunication Networks by Simulation -- Author Index.…”
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  19. 199

    Learning-based local visual representation and indexing by Rongrong, Ji, Yao, Hongxun, Gao, Yue, Duan, Ling-Yu, Dai, Qionghai

    Published 2014
    Table of Contents: “…3.4.1 Cross-database Case3.4.2 Incremental Transfer; 3.5 Experiments; 3.5.1 Quantitative results; 3.6 Summary; Chapter 4: Supervised Dictionary Learning via Semantic Embedding ; 4.1 Introduction; 4.2 Semantic Labeling Propagation; 4.2.1 Density Diversity Estimation ; 4.3 Supervised Dictionary Learning; 4.3.1 Generative Modeling ; 4.3.2 Supervised Quantization ; 4.4 Experiments; 4.4.1 Database and Evaluations; 4.4.2 Quantitative Results; 4.5 Summary; Chapter 5: Visual Pattern Mining; 5.1 Introduction; 5.2 Discriminative 3D Pattern Mining; 5.2.1 The Proposed Mining Scheme.…”
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