Search Results - (((((((want OR giant) OR semantic) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

Navigation signal processing for GNSS software receivers by Pany, Thomas

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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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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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Language and logos : studies in theoretical and computational linguistics

Table of Contents: “…CONTENTS -- Preface -- Part I Syntax -- A Spurious Genitive Puzzle in Polish -- Semantic Type Effects on Crossing Movement in German -- Me and Chomsky -- On the Typology of Verb Second -- Movement from Verb-Second Clauses Revisited -- Spurious Ambiguities and the Parentheticals Debate -- Part II Semantics -- On Squeamishness of the Royal Kind -- Information Structure of schon -- When- Clauses, Factive Verbs and Correlates -- The Proof Theory of Partial Variables -- Brentano's Apple -- How to Interpret Expletive Negation under bevor in German…”
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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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OIPE 2012

Table of Contents: “…Optimization of EMI filters for electrical drives in aircraftAdaptive level set method for accurate boundary shape in optimization of electromagnetic systems; Amodified immune algorithm with spatial filtering for multiobjective topology optimisation of electromagnetic devices; Use of compensation theorem for the robustness assessment of electromagnetic devices optimal design; Multi-physics optimisation of an energy harvester device for automotive application; Stochastic modeling error reduction using Bayesian approach coupled with an adaptive Kriging-based model.…”
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New autonomous systems by Cardon, Alain, 1946-, Itmi, Mhamed

Table of Contents: “…Intro -- Table of Contents -- Title -- Copyright -- Introduction -- List of Algorithms -- 1 Systems and their Design -- 1.1. Modeling systems -- 1.2. …”
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Enterprise AI for Dummies. by Jarvinen, Zachary

Table of Contents: “…External partnerships -- The importance of executive buy-in -- Weighing Your Options: Build versus Buy -- When you should do it yourself -- When you should partner with a provider -- Hosting in the Cloud versus On Premises -- What the cloud providers say -- What the hardware vendors say -- The truth in the middle -- Part 2 Exploring Vertical Market Applications -- Chapter 5 Healthcare/HMOs: Streamlining Operations -- Surfing the Data Tsunami -- Breaking the Iron Triangle with Data -- Matching Algorithms to Benefits -- Examining the Use Cases -- Delivering lab documents electronically…”
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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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Solutions in lidar profiling of the atmosphere by Kovalev, Vladimir A.

Table of Contents: “…1.6.1 Algorithm and Solution Uncertainty1.6.2 Numerical Simulations and Experimental Data; 1.7 Examination of the Remaining Offset in the Backscatter Signal by~Analyzing the Shape of the Integrated Signal; 1.8 Issues in the Examination of the Lidar Overlap Function; 1.8.1 Influence of Distortions in the Lidar Signal when Determining the~Overlap Function; 1.8.2 Issues of Lidar Signal Inversion within the Incomplete Overlap Area; Chapter 2 Essentials and Issues in Separating the Backscatter and Transmission Terms in The Lidar Equation.…”
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Frontiers in Massive Data Analysis. by Council, National Research

Table of Contents: “…FrontMatter -- Acknowledgments -- Contents -- Summary -- 1 Introduction -- 2 Massive Data in Science, Technology, Commerce, National Defense, Telecommunications, and Other Endeavors -- 3 Scaling the Infrastructure for Data Management -- 4 Temporal Data and Real-Time Algorithms -- 5 Large-Scale Data Representations -- 6 Resources, Trade-offs, and Limitations -- 7 Building Models from Massive Data -- 8 Sampling and Massive Data -- 9 Human Interaction with Data -- 10 The Seven Computational Giants of Massive Data Analysis -- 11 Conclusions -- Appendixes…”
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F♯ for Machine Learning Essentials. by Mukherjee, Sudipta

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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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Quantum Computation and Information. by Lomonaco, Samuel J.

Table of Contents: “…Vintage Simon quantum hidden subgroup algorithms (QHSAs)Part 5. Vintage Shor Algorithms -- 11. …”
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Advances in Pattern Recognition : Proceedings of the Sixth International Conference.

Table of Contents: “…Biometrics; Clustering Algorithms; Document Analysis; Image Registration and Transmission; Image Segmentation; Multimedia Object Retrieval; Pattern Recognition; Shape Recognition; Speech and 1-D Signal Analysis and Texture Analysis.…”
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Development of Modern Statistics and Related Topics : In Celebration of Prof Yaoting Zhang's 70th Birthday. by Zhang, Heping

Table of Contents: “…Estimation When Variances Are Known ; 4. Estimation when variances are Unknown ; 5. …”
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Differential and Differential-Algebraic Systems for the Chemical Engineer : Solving Numerical Problems. by Buzzi-Ferraris, Guido

Table of Contents: “…1.10 Adaptive Methods1.10.1 Method Derived from the Gauss-Kronrod Algorithm; 1.10.2 Method Derived from the Extended Trapezoid Algorithm; 1.10.3 Method Derived from the Gauss-Lobatto Algorithm; 1.11 Parallel Computations; 1.12 Classes for Definite Integrals; 1.13 Case Study: Optimal Adiabatic Bed Reactors for Sulfur Dioxide with Cold Shot Cooling; 2 Ordinary Differential Equations Systems; 2.1 Introduction; 2.2 Algorithm Accuracy; 2.3 Equation and System Conditioning; 2.4 Algorithm Stability; 2.5 Stiff Systems; 2.6 Multistep and Multivalue Algorithms for Stiff Systems.…”
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OpenCV Android Programming By Example. by Muhammad, Amgad

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What intelligence tests miss : the psychology of rational thought by Stanovich, Keith E., 1950-

Table of Contents: “…Inside George W. Bush's mind : hints at what IQ tests miss -- Dysrationalia : separating rationality and intelligence -- The reflective mind, the algorithmic mind, and the autonomous mind -- Cutting intelligence down to size -- Why intelligent people doing foolish things is no surprise -- The cognitive miser : ways to avoid thinking -- Framing and the cognitive miser -- Myside processing : heads I win, tails I win too! …”
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Mastering D3.js. by Castillo, Pablo Navarro

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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