Search Results - (((((((kant OR wants) OR semantic) OR file) OR cantor) OR anne) OR shape) OR hints) algorithms.

Basic data analysis for time series with R by Derryberry, DeWayne R.

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MATLAB for Machine Learning. by Ciaburro, Giuseppe

Table of Contents: “…; Data mining and data visualization; Regression analysis; Classification; Cluster analysis; Dimensionality reduction; Neural Network Toolbox; Statistics and algebra in MATLAB; Summary; Chapter 2: Importing and Organizing Data in MATLAB; Familiarizing yourself with the MATLAB desktop; Importing data into MATLAB; The Import Wizard; Importing data programmatically; Loading variables from file; Reading an ASCII-delimited file; Comma-separated value files; Importing spreadsheets.…”
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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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Comprehensive Ruby Programming. by Hudgens, Jordan

Table of Contents: “…-- A better way -- SOLID OOP development -- the Liskov substitution principle -- The LSP definition -- Breaking down the LSP -- The LSP example -- The problem -- The LSP violation -- The fix -- SOLID OOP development -- the interface segregation principle -- The ISP definition -- The ISP code example -- Introducing the moderator -- A better way -- The result -- A caveat -- SOLID OOP development -- the dependency inversion principle -- The DIP in the real world -- The DIP definition -- The DIP code example -- Recap -- Summary -- Chapter 10: Working with the Filesystem in Ruby -- Creating a file -- Ruby File class -- Other options you can pass as the second option -- Reading files into a program using the File class -- Deleting a file -- Appending a file.…”
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Evolutionary optimization

Table of Contents: “…Cover -- Contents -- Preface -- Contributing Authors -- Part I Introduction -- 1 Conventional Optimization Techniques -- 1 Classifying Optimization Models -- 2 Linear Programming -- 3 Goal Programming -- 4 Integer Programming -- 5 Nonlinear Programming -- 6 Simulation -- 7 Further Reading -- 2 Evolutionary Computation -- 1 What Is Evolutionary Computation -- 2 A Brief Overview of Evolutionary Computation -- 3 Evolutionary Algorithm and Generate-and-Test Search Algorithm -- 4 Search Operators -- 5 Summary -- Part II Single Objective Optimization -- 3 Evolutionary Algorithms and Constrained Optimization -- 1 Introduction -- 2 General considerations -- 3 Numerical optimization -- 4 Final Remarks -- 4 Constrained Evolutionary Optimization -- 1 Introduction -- 2 The Penalty Function Method -- 3 Stochastic Ranking -- 4 Global Competitive Ranking -- 5 How Penalty Methods Work -- 6 Experimental Study -- 7 Conclusion -- Appendix: Test Function Suite -- Part III Multi-Objective Optimization -- 5 Evolutionary Multiobjective Optimization -- 1 Introduction -- 2 Definitions -- 3 Historical Roots -- 4 A Quick Survey of EMOO Approaches -- 5 Current Research -- 6 Future Research Paths -- 7 Summary -- 6 MEA for Engineering Shape Design -- 1 Introduction -- 2 Multi-Objective Optimization and Pareto-Optimality -- 3 Elitist Non-dominated Sorting GA (NSGA-II) -- 4 Hybrid Approach -- 5 Optimal Shape Design -- 6 Simulation Results -- 7 Conclusion -- 7 Assessment Methodologies for MEAs -- 1 Introduction -- 2 Assessment Methodologies -- 3 Discussion -- 4 Comparing Two Algorithms: An Example -- 5 Conclusions and Future Research Paths -- Part IV Hybrid Algorithms -- 8 Hybrid Genetic Algorithms -- 1 Introduction -- 2 Hybridizing GAs with Local Improvement Procedures -- 3 Adaptive Memory GA's -- 4 Summary -- 9 Combining choices of heuristics -- 1 Introduction -- 2 GAs and parameterised algorithms -- 3 Job Shop Scheduling -- 4 Scheduling chicken catching -- 5 Timetabling -- 6 Discussion and future directions -- 10 Nonlinear Constrained Optimization -- 1 Introduction -- 2 Previous Work -- 3 A General Framework to look for SPdn -- 4 Experimental Results -- 5 Conclusions -- Part V Parameter Selection in EAs -- 11 Parameter Selection -- 1 Introduction -- 2 Parameter tuning vs. parameter control -- 3 An example -- 4 Classification of Control Techniques -- 5 Various forms of control -- 6 Discussion -- Part VI Application of EAs to Practical Problems -- 12 Design of Production Facilities -- 1 Introduction -- 2 Design for Material Flow When the Number of I/O Points is Unconstrained -- 3 Design for Material Flow for a Single I/O Point -- 4 Considering Intradepartmental Flow -- 5 Material Handling System Design -- 6 Concluding Remarks -- 13 Virtual Population and Acceleration Techniques -- 1 Introduction -- 2 Concept of Virtual Population -- 3 Solution Acceleration Techniques -- 4 Accelerated GA and Acceleration Sche.…”
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Cybernetic Intelligence

Table of Contents: “…Editorial advisory board; Preface; Editorial; Second-order cybernetics and enactive perception; Semantic category theory cognition and conceptual reference; Bipolar logic and probabilistic interpretation; Cooperative clans; Future reasoning machines: mind and body; Machine vision methods for autonomous micro-robotic systems; Optimisation enhancement using self-organising fuzzy control; Intelligent agents and distributed models for cooperative task support; Landscape classification and problem specific reasoning for genetic algorithms; Business cybernetics: a provocative suggestion.…”
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F♯ for Machine Learning Essentials. by Mukherjee, Sudipta

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Optimal structural design : contact problems and high-speed penetration by Banichuk, Nikolaĭ Vladimirovich, Ivanova, S. I︠U︡. (Svetlana I︠U︡rʹevna)

Table of Contents: “…Shape optimization of punch moving with friction; 4. …”
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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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Medical and Care Compunetics 2 : Medical and Care Compunetics 2. by Bos, L.

Table of Contents: “…Standardized Semantic Markup for Reference Terminologies, Thesauri and Coding Systems: Benefits for Distributed E-Health ApplicationsDevelopment of an Expert System for Classification of Medical Errors; Model of Good Practice Tools for Risk Reduction and Clinical Governance; Optimisation Issues of High Throughput Medical Data and Video Streaming Traffic in 3G Wireless Environments; A New Algorithm for Content-Based Region Query in Databases with Medical Images; Economic Impact of Telemedicine: A Survey.…”
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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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The the Python Workshop : a Practical, No-Nonsense Introduction to Python Development. by Bird, Andrew

Table of Contents: “…Table of ContentsVital Python - Math, Strings, Conditionals, and LoopsPython StructuresExecuting Python - Programs, Algorithms, and FunctionsExtending Python, Files, Errors, and GraphsConstructing Python - Classes and MethodsThe Standard LibraryBecoming PythonicSoftware DevelopmentPractical Python - Advanced TopicsData Analytics with pandas and NumPyMachine Learning.…”
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Digital holography by Picart, Pascal

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The finite element method : its basis and fundamentals by Zienkiewicz, O. C.

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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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Intelligent Technologies : From Theory to Applications - The New Trends in Computational Intelligence. by Kvasnicka, V.

Table of Contents: “…Neural Networks; Superconvergence Concept in Machine Learning; Application of the Parallel Population Learning Algorithm to Training Feed-forward ANN; Markovian Architectural Bias of Recurrent Neural Networks; SOFM Training Speedup; Generalized Forecasting Sigma-Pi Neural Network; Human Centered Intelligent Robots Using "Ontological Neural Network"; Trajectory Bounds of Solutions of Delayed Cellular Neural Networks Differential Systems; From Plain to Modular Topology: Automatic Modularization of Structured ANNs.…”
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TensorFlow Reinforcement Learning Quick Start Guide : Get up and Running with Training and Deploying Intelligent, Self-Learning Agents Using Python. by Balakrishnan, Kaushik

Table of Contents: “…Learning the theory behind a DQNUnderstanding target networks; Learning about replay buffer; Getting introduced to the Atari environment; Summary of Atari games; Pong; Breakout; Space Invaders; LunarLander; The Arcade Learning Environment ; Coding a DQN in TensorFlow; Using the model.py file; Using the funcs.py file; Using the dqn.py file; Evaluating the performance of the DQN on Atari Breakout; Summary; Questions; Further reading; Chapter 4: Double DQN, Dueling Architectures, and Rainbow; Technical requirements; Understanding Double DQN ; Coding DDQN and training to play Atari Breakout…”
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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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Stairs 2006 : Proceedings of the Third Starting AI Researchers' Symposium

Table of Contents: “…A Comparison of Two Machine-Learning Techniques to Focus the Diagnosis TaskArgumentation Semantics for Temporal Defeasible Logic; NEWPAR: An Optimized Feature Selection and Weighting Schema for Category Ranking; Challenges and Solutions for Hierarchical Task Network Planning in E-Learning; Invited Talks; Artificial Intelligence and Unmanned Aerial Vehicles; Writing a Good Grant Proposal; Author Index…”
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