Search Results - (((((((ant OR want) OR semantic) OR win) OR cantor) OR anne) OR shape) OR hints) algorithms.

Anaphora Resolution. by Mitkov, Ruslan

Table of Contents: “…2.1.2 Syntactic knowledge2.1.3 Semantic knowledge; 2.1.4 Discourse knowledge; 2.1.5 Real-world (common-sense) knowledge; 2.2 Anaphora resolution in practice; 2.2.1 Identification of anaphors; 2.2.1.1 Identification of anaphoric pronouns; 2.2.1.2 Identification of anaphoric noun phrases; 2.2.1.3 Tools and resources for the identification of anaphors; 2.2.2 Location of the candidates for antecedents; 2.2.2.1 The search scope of candidates for antecedent; 2.2.2.2 Tools and resources needed for the location of potential candidates; 2.2.3 The resolution algorithm: factors in anaphora resolution.…”
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Enterprise AI for Dummies. by Jarvinen, Zachary

Table of Contents: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Strong, Weak, General, and Narrow -- Foolish Assumptions -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Exploring Practical AI and How It Works -- Chapter 1 Demystifying Artificial Intelligence -- Understanding the Demand for AI -- Converting big data into actionable information -- Relieving global cost pressure -- Accelerating product development and delivery -- Facilitating mass customization -- Identifying the Enabling Technology -- Processing -- Algorithms…”
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Recent Advances in Natural Language Processing : Selected Papers from RANLP'95

Table of Contents: “…An augmented Earley algorithm for repair; 5.1 String representations; 5.2 Augmentations to the standard algorithm; 5.3 The augmented algorithm; 5.4 Remarks; 6 Conclusion; REFERENCES; Parsing for Targeted Errors in Controlled Languages; Abstract; 1. …”
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An introduction to computational engineering with Matlab by Yang, Xin-She

Table of Contents: “…Optimization in Engineering -- 12.1 Introduction -- 12.2 Bioinspired Algorithms -- 12.2.1 Genetic Algorithms -- 12.2.2 Neural Networks…”
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Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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Optimization advances in electric power systems

Table of Contents: “…Unreliability Costs -- 3.5. Proposed Algorithms -- 3.5.1. ES and TS Algorithms -- 3.5.2. …”
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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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Tales of Literacy for the 21st Century : the Literary Agenda. by Wolf, Maryanne

Table of Contents: “…; Deep reading and what comes next; A first algorithm for what comes next; Notes; 7: A Tale of Hope for Non-Literate Children.…”
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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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Principles of Quantum Computation and Information, Volume I : Basic Concepts. by Casati, Giulio, Strini, Giuliano

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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

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Challenges and opportunities of HealthGrids : proceedings of Healthgrid 2006

Table of Contents: “…Early Diagnosis of Alzheimer's Disease Using a Grid Implementation of Statistical Parametric Mapping AnalysisUsing the Grid to Analyze the Pharmacokinetic Modelling After Contrast Administration in Dynamic MRI; Medical Image Registration Algorithms Assessment: Bronze Standard Application Enactment on Grids Using the MOTEUR Workflow Engine; Ethical, Legal and Privacy Issues on HealthGrids; The Ban on Processing Medical Data in European Law: Consent and Alternative Solutions to Legitimate Processing of Medical Data in HealthGrid.…”
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Java Data Mining - Strategy, Standard, and Practice : a Practical Guide for architecture, design, and implementation. by Hornick, Mark F.

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Spatial capture-recapture

Table of Contents: “…3.3 Characterizing Posterior Distributions by MCMC Simulation3.3.1 What goes on under the MCMC hood; 3.3.2 Rules for constructing full conditional distributions; 3.3.3 Metropolis-Hastings algorithm; 3.4 Bayesian Analysis Using the BUGS Language; 3.4.1 Linear regression in WinBUGS; 3.5 Practical Bayesian Analysis and MCMC; 3.5.1 Choice of prior distributions; 3.5.2 Convergence and so forth; 3.5.3 Bayesian confidence intervals; 3.5.4 Estimating functions of parameters; 3.6 Poisson GLMs; 3.6.1 North American breeding bird survey data; 3.6.2 Poisson GLM in WinBUGS.…”
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Seismic Data Interpretation using Digital Image Processing by Al-Shuhail, Abdullatif A., Al-Dossary, Saleh A., Mousa, Wail A.

Table of Contents: “…5.5 Two-Dimensional Second-Order Derivative Operator5.5.1 The Coherence Attribute; 5.5.2 The Dip Attribute; 5.6 The Curvature Attribute; 5.7 Curvature of the Surface; 5.7.1 Curve, Velocity, and Curvature; 5.7.2 Surface, Tangent Plane, and Norm; 5.8 Shape Operator, Normal Curvature, and Principal Curvature; 5.8.1 Normal Curvature; 5.8.2 Shape Operator; 5.8.3 The Principal Curvatures; 5.8.4 Calculation of the Principal Curvatures; 5.8.5 Summary of Calculation of Principal Curvature for a Surface; 5.9 The Randomness Attribute; 5.10 Technique for Two-Dimensional Images.…”
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Building Machine Learning Systems with Python. by Richert, Willi

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Ranking the Liveability of the World's Major Cities : the Global Liveable Cities Index (GLCI). by Tan, Khee Giap

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Data clustering in C++ : an object-oriented approach by Gan, Guojun, 1979-

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Iaeng transactions on electrical engineering. Vol. 1, Special issue of the International Multiconference of Engineers and Computer Scientists 2012

Table of Contents: “…Pawar -- Web services for chronic pain monitoring / Nuno Goncalo Coelho Costa Pombo, Pedro Jose Guerra de Araujo and Joaquim Manuel Vieira da Silva Viana -- Parallel binomial American option pricing on CPU-GPU hybrid platform / Nan Zhang, Chi-Un Lei and Ka Lok Man -- The subsystem grouping scheme using use case dependency graph and domain-specific semantic model for large complex systems / Nanchaya Khrueahong and Wiwat Vatanawood -- MOBM: a methodology for building practical domain ontologies from database information / Minyoung Ra [and others] -- A trial of the dynamic weighted sum method for multi-objective optimization / Hong Zhang -- A multi-agent platform to manage distributed and heterogeneous knowledge by using semantic web / Inaya Lahoud [and others] -- An intelligent train marshaling based on the processing time considering group layout of freight cars / Yoichi Hirashima -- A web-based multilingual intelligent tutor system based on Jackson's learning styles profiler and expert systems / H. …”
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Artificial intelligence research and development : recent advances and applications

Table of Contents: “…Title Page -- Preface -- Conference Organization -- Contents -- Machine Learning -- Approximate Policy Iteration with Bellman Residuals Minimization -- A Randomized Algorithm for Exact Transduction -- Comparing Feature-Based and Distance-Based Representations for Classification Similarity Learning -- Computer Vision I -- Bag-of-Tracklets for Person Tracking in Life-Logging Data -- Improving Autonomous Underwater Grasp Specification Using Primitive Shape Fitting in Point Clouds -- Emotions Classification Using Facial Action Units Recognition…”
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