Search Results - (((((((want OR pants) OR wanting) OR markant) OR cantor) OR anne) OR shape) OR hints) algorithms.

Regularization, optimization, kernels, and support vector machines

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Optimization theory and related topics : Israel mathematical conference proceedings : a workshop in memory of Dan Butnariu, January 11-14, 2010, Haifa, Israel

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When life is linear : from computer graphics to bracketology by Chartier, Timothy P.

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Satellite networking : principles and protocols by Sun, Zhili

Table of Contents: “…Traffic Shaping --…”
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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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OpenCV with Python by example : build real-world computer vision applications and develop cool demos using OpenCV for Python by Joshi, Prateek

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Handbook of performability engineering

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Computational mechanics of discontinua by Munjiza, Antonio A.

Table of Contents: “…Front Matter -- Introduction to Mechanics of Discontinua -- Methods of Mechanics of Discontinua -- Disc to Edge Contact Interaction in 2D -- Triangle to Edge Contact Interaction in 2D -- Ball to Surface Contact Interaction in 3D -- Tetrahedron to Points Contact Interaction in 3D -- Tetrahedron to Triangle Contact Interaction in 3D -- Rock Joints -- MR Contact Detection Algorithm for Bodies of Similar Size -- MR Contact Detection Algorithm for Bodies of Different Sizes -- MR Contact Detection Algorithm for Complex Shapes in 2D -- MR Contact Detection Algorithm for Complex Shapes in 3D -- Parallelization.…”
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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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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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F♯ for Machine Learning Essentials. by Mukherjee, Sudipta

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OpenCV Android Programming By Example. by Muhammad, Amgad

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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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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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On the Shoulders of Giants : New Approaches to Numeracy.

Table of Contents: “…""Mirror Geometry""""Using Symmetry""; ""Lattices""; ""Dissection""; ""Combinatorial Tools""; ""REPRESENTATION""; ""Models""; ""Maps""; ""Shadows and Lenses""; ""Drawing""; ""Image Reconstruction""; ""Computer Graphics""; ""VISUALIZATION""; ""CURRICULAR ISSUES""; ""Forging Connections""; ""Geometry""; ""Studying Shape""; ""The Study of Shape is Interdisciplinary""; ""The Study of Shape is a Laboratory Subject""; ""The Study of Shape is for Everyone""; ""The Study of Shape is Fun""; ""The Study of Shape is Open Ended""; ""REFERENCES AND RECOMMENDED READING""; ""Change""…”
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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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