Search Results - (((((((want OR wanting) OR semantic) OR find) OR cantor) OR anne) OR blaney) OR hints) algorithms.

Media technologies : essays on communication, materiality, and society

Table of Contents: “…Bowker -- "What Do We Want?" "Materiality!" "When Do We Want It?" "Now!" …”
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Handbook of Mathematical Induction. by Gunderson, David S.

Table of Contents: “…Chapter 14: Logic and languageChapter 15: Graphs; Chapter 16: Recursion and algorithms; Chapter 17: Games and recreations; Chapter 18: Relations and functions; Chapter 19: Linear and abstract algebra; Chapter 20: Geometry; Chapter 21: Ramsey theory; Chapter 22: Probability and statistics; Part III: Solutions and hints to exercises; Chapter 23: Solutions: Foundations; Chapter 24: Solutions: Inductive techniques applied to the infinite; Chapter 25: Solutions: Paradoxes and sophisms; Chapter 26: Solutions: Empirical induction; Chapter 27: Solutions: Identities.…”
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Pattern discovery in biomolecular data : tools, techniques, and applications

Table of Contents: “…Discovering patterns in DNA sequences by the algorithmic significance method / Aleksandar Milosavljevic -- Assembling blocks / Jorja G. …”
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Artificial neural systems : principle and practice by Lorrentz, Pierre

Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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Digital journalism, drones, and automation : the language and abstractions behind the news by Dowd, Cate

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Artificial intelligence with Python : build real-world artificial intelligence applications with Python to intelligently interact with the world around you by Joshi, Prateek

Table of Contents: “…; Clustering data with K-Means algorithm; Estimating the number of clusters with Mean Shift algorithm; Estimating the quality of clustering with silhouette scores; What are Gaussian Mixture Models?…”
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Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn by Hackeling, Gavin

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Modeling Reality : How Computers Mirror Life. by Białynicki-Birula, Iwo

Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
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Navigation signal processing for GNSS software receivers by Pany, Thomas

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Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios, 1951-

Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
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Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

Table of Contents: “…Method resolution orderSuper's superpowers; Using language protocols in classes; Iteration protocol; Context manager protocol; Using abstract classes; Summary; Chapter 3: Functions and Utilities; Defining functions; Decorating callables; Utilities; Summary; Chapter 4: Data Structures and Algorithms; Python built-in data structures; Python library data structures; Third party data structures; Arrays/List; Binary tree; Sorted containers; Trie; Algorithms on scale; Summary; Chapter 5: Elegance with Design Patterns; Observer pattern; Strategy pattern; Singleton pattern; Template pattern.…”
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Compressed sensing : theory and applications

Table of Contents: “…Graphical models concepts in compressed sensing / Andrea Montanari -- 10. Finding needles in compressed haystacks / Robert Calderbank and Sina Jafarpour -- 11. …”
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Stairs 2006 : Proceedings of the Third Starting AI Researchers' Symposium

Table of Contents: “…Binarization Algorithms for Approximate Updating in Credal NetsOn Generalizing the AGM Postulates; The Two-Variable Situation Calculus; Base Belief Change and Optimized Recovery; Unsupervised Word Sense Disambiguation Using the WWW; Relational Descriptive Analysis of Gene Expression Data; Solving Fuzzy PERT Using Gradual Real Numbers; Approaches to Efficient Resource-Constrained Project Rescheduling; A Comparison of Web Service Interface Similarity Measures; Finding Alternatives Web Services to Parry Breakdowns; Posters; Smart Ride Seeker Introductory Plan…”
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Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost by Mukherjee, Arindam

Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
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Principles of Quantum Computation and Information, Volume I : Basic Concepts. by Casati, Giulio, Strini, Giuliano

Table of Contents: “…Quantum phase estimation. 3.13. Finding eigenvalues and eigenvectors. 3.14. Period finding and Shor's algorithm. 3.15. …”
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Advances in intelligent IT : active media technology 2006

Table of Contents: “…Title page; Preface; Organization; Contents; Keynotes; Active Media Technologies (AMT) from the Standpoint of the Wisdom Web; Anytime Learning and Classification for Online Applications; Domain-Driven Data Mining: Methodologies and Applications; Regular Papers; Web Service Request Transformatter; A Head-Tracker Based on the Lucas-Kanade Optical Flow Algorithm; A Fair Peer Selection Algorithm for an Ecommerce-Oriented Distributed Recommender System; Intelligent Decision Making with the Semantic Web; Relevence Assessment of Topic Ontology; Information Extraction from a Whole Web Site.…”
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Ant colony optimization by Dorigo, Marco

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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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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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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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