Search Results - (((((((ant OR canton) OR semantic) OR mind) OR cantor) OR anne) OR slane) OR hints) algorithms.

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

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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DSP with Python Programming. by Charbit, Maurice

Table of Contents: “…Gaussian linear case: Kalman algorithm; 3.5. Discrete finite Markov case; 4 Monte-Carlo Methods; 4.1. …”
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Artificial intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques. by Deshpande, Anand

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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Process Control : a Practical Approach. by King, Michael

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Focus on artificial neural networks

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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Implementing cryptography using Python by Bray, Shannon, 1972-

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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Metaheuristics for vehicle routing problems. by Labadie, Nacima

Table of Contents: “…Memetic algorithm; 4.1.3. Memetic algorithm with population management; 4.1.4. …”
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Industrial control systems

Table of Contents: “…EXTRACTIVE FERMENTATION PROCESS FOR BIOETHANOL PRODUCTION ; 3. PLANT MODEL BASED ON ANN ; 3.1. ANN Configurations.…”
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The Decisionist Imagination : Sovereignty, Social Science and Democracy in the 20th Century. by Guilhot, Nicolas

Table of Contents: “…Reading the International Mind; Chapter 2. Militant Democracy as Decisionist Liberalism; Chapter 3. …”
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Kernels for structured data by Gärtner, Thomas

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Communicating process architectures 2002. by World Occam And Transputer User Group. Technical Meeting (25th: 2002: University Of Reading, U. K.)

Table of Contents: “…A Communicating Threads (CT) Case Study: JIWYPrioritised Dynamic Communicating Processes -- Part I; Prioritised Dynamic Communicating Processes -- Part II; Implementing a Distributed Algorithm for Detection of Local Knots and Cycles in Directed Graphs; Author Index.…”
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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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Computational models of argument : Proceedings of COMMA 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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Automata and Computability. by Kozen, Dexter, 1951-

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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Mathematical morphology and its applications to image and signal processing

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

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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Media Backends : Digital Infrastructures and Sociotechnical Relations. by Parks, Lisa

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Java programming interviews exposed by Markham, Noel

Table of Contents: “…Chapter 18: Useful LibrariesRemoving Boilerplate Code with Apache Commons; Developing with Guava Collections; Using Joda Time; Summary; Chapter 19: Developing with Build Tools; Building Applications with Maven; Ant; Summary; Chapter 20: Android; Basics; User Interface; Persistence; Android Hardware; Summary; Appendix: Introducing Scala; Scala Basics; Functions as Values; Immutability; Summary; Index.…”
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The data imperative : how digitalization is reshaping management, organizing, and work by Schildt, Henri

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Big Data, IoT, and Machine Learning : Tools and Applications. by Agrawal, Rashmi

Table of Contents: “…Chapter 3 Reviews Analysis of Apple Store Applications Using Supervised Machine Learning -- 3.1 Introduction -- 3.2 Literature Review -- 3.2.1 Machine Learning Algorithms -- 3.2.2 Feature Extraction Algorithms -- 3.3 Proposed Methodology -- 3.3.1 Data Collection -- 3.3.2 Feature Extraction -- 3.3.3 Data Analysis and Sentiment Analysis -- Text Processing -- 3.3.4 Text Normalisation -- 3.4 Feature Extraction Algorithm -- 3.4.1 CountVectorizer -- 3.4.2 TfidfVectorizer (TF-IDF) -- 3.5 Supervised ML Classification -- 3.6 Experiment Design -- 3.7 Experimental Results and Analysis…”
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