Search Results - (((((((ant OR wanted) OR semantics) OR arts) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

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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The Johns Hopkins guide to digital media

Table of Contents: “…Robertson -- Search / Yuk Hui -- Searle's Chinese Room / Inderjeet Mani -- Self-reflexivity in electronic art / Winfried Nöth -- Semantic web / Axel-Cyrille Ngonga Ngomo -- Simulation / Gonzalo Frasca -- Social Network Sites (SNSs) / Olga Goriunova and Chiara Bernardi -- Software studies / Matthew Fuller -- Sound / Aaron Angello -- Spatiality of digital media / Marie-Laure Ryan -- Story generation / Pablo Gervás -- Storyspace / Anja Rau -- Subversion (creative destruction) / Davin Heckman -- Temporality of digital works / John David Zuern -- Transmedial fiction / Christy Dena -- Turing test / Ragnhild Tronstad -- Twitter, Tumblr, and Microblogging / Brian Croxall -- Video / Patrick Vonderau -- Viral aesthetics / Jussi Parikka -- Virtual bodies / Marco Caracciolo -- Virtual economics / Edward Castronova and Travis L. …”

Graph Partitioning. by Bichot, Charles-Edmond

Table of Contents: “…Hendrickson-Leland coarsening algorithm; 2.3.4. The Heavy Edge Matching (HEM) algorithm; 2.4. …”
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Gradience in grammar : generative perspectives

Table of Contents: “…Frisch and Adrienne Stearns -- Intermediate syntactic variants in a dialect : standard speech repertoire and relative acceptability / Leonie Cornips -- Gradedness and optionality in mature and developing grammars / Antonella Sorace -- Decomposing gradience : quantitative versus qualitative distinctions / Matthias Schlesewsky, Ina Bornkessel, and Brian McElree -- Gradient perception of intonation / Caroline Féry and Ruben Stoel -- Prototypicality judgements as inverted perception / Paul Boersma -- Modelling productivity with the gradual learning algorithm : the problem of accidentally exceptionless generalizations / Adam Albright and Bruce Hayes -- Gradedness as relative efficiency in the processing of syntax and semantics / John A. …”
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Particle swarm optimisation : classical and quantum perspectives by Sun, Jun, 1971-

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There's Something about Gödel : The Complete Guide to the Incompleteness Theorem. by Berto, Francesco

Table of Contents: “…. -- 6 ... and the unsatisfied logicists, Frege and Russell -- 7 Bits of set theory -- 8 The Abstraction Principle -- 9 Bytes of set theory -- 10 Properties, relations, functions, that is, sets again -- 11 Calculating, computing, enumerating, that is, the notion of algorithm…”
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Real-time database systems : architecture and techniques

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Theoretical Computer Science : Proceedings of the 10th Italian Conference on ICTCS '07. by Italiano, Giuseppe F.

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Optics and artificial vision by González-Acuäna, Rafael G., Chaparro-Romo, Héctor A., Melendez-Montoya, Israel

Table of Contents: “…Introduction -- 3.2. The Lucas-Kanade algorithm -- 3.3. Application of the Lucas-Kanade algorithm and its Python code -- 3.4. …”
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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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Handbook on semidefinite, conic and polynomial optimization

Table of Contents: “…Lasserre and Mihai Putinar -- Self-regular interior-point methods for semidefinite optimization / Maziar Salahi and Tamás Terlaky -- Elementary optimality conditions for nonlinear SDPs / Florian Jarre -- Recent progress in interior-point methods: cutting-plane algorithms and warm starts / Alexander Engau -- Exploiting sparsity in SDP relaxation of polynomial optimization problems / Sunyoung Kim and Masakazu Kojima -- Block coordinate descent methods for semidefinite programming / Zaiwen Wen, Donald Goldfarb, and Katya Scheinberg -- Projection methods in conic optimization / Didier Henrion and Jérôme Malick -- SDP relaxations for non-commutative polynomial optimization / Miguel Navascués, Stefano Pironio, and Antonio Acín -- Semidefinite programming and constraint programming / Willem-Jan van Hoeve -- The state-of-the-art in conic optimization software / Hans D. …”
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The virtual life of film by Rodowick, David Norman

Table of Contents: “…Film begets video -- The death of cinema and the birth of film studies -- A medium in all things -- Automatisms and art -- Automatism and photography -- Succession and the film strip -- Ways of worldmaking -- A world past -- An ethics of time -- III. …”
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Cognitive Electronic Warfare : An Artificial Intelligence Approach. by Haigh, Karen

Table of Contents: “…-- 1.5 Reader's Guide -- 1.6 Conclusion -- References -- 2 Objective Function -- 2.1 Observables That Describe the Environment -- 2.1.1 Clustering Environments -- 2.2 Control Parameters to Change Behavior -- 2.3 Metrics to Evaluate Performance -- 2.4 Creating a Utility Function -- 2.5 Utility Function Design Considerations -- 2.6 Conclusion -- References -- 3 ML Primer -- 3.1 Common ML Algorithms -- 3.1.1 SVMs -- 3.1.2 ANNs -- 3.2 Ensemble Methods -- 3.3 Hybrid ML -- 3.4 Open-Set Classification -- 3.5 Generalization and Meta-learning -- 3.6 Algorithmic Trade-Offs -- 3.7 Conclusion -- References -- 4 Electronic Support -- 4.1 Emitter Classification and Characterization -- 4.1.1 Feature Engineering and Behavior Characterization -- 4.1.2 Waveform Classification -- 4.1.3 SEI -- 4.2 Performance Estimation -- 4.3 Multi-Intelligence Data Fusion -- 4.3.1 Data Fusion Approaches -- 4.3.2 Example: 5G Multi-INT Data Fusion for Localization -- 4.3.3 Distributed-Data Fusion -- 4.4 Anomaly Detection -- 4.5 Causal Relationships -- 4.6 Intent Recognition -- 4.6.1 Automatic Target Recognition and Tracking -- 4.7 Conclusion -- References -- 5 EP and EA -- 5.1 Optimization -- 5.1.1 Multi-Objective Optimization -- 5.1.2 Searching Through the Performance Landscape -- 5.1.3 Optimization Metalearning -- 5.2 Scheduling -- 5.3 Anytime Algorithms -- 5.4 Distributed Optimization -- 5.5 Conclusion.…”
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Big data in medical science and healthcare management : diagnosis, therapy, side effects

Table of Contents: “…Autopilot and "doctor algorithm"? -- 1. Intro big data for healthcare? / Peter Langkafel -- 2. …”
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The Fifth Decade of Cardiac Pacing. by Barold, S. Serge

Table of Contents: “…; 11 Permanent and Temporary Single-Lead VDD and DDD Pacing: State of the Art; 12 Pacemaker Memory: Basic Concepts and New Technology; 13 Future Trends in Pacemaker Technology; 14 Diagnosis of Supraventricular Tachyarrhythmias by Automatic Mode-Switching Algorithms of Dual-Chamber Pace.…”
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Digital signal processing with kernel methods by Rojo-Álvarez, José Luis, 1972-, Martínez-Ramón, Manel, 1968-, Muñoz Marí, Jordi, Camps-Valls, Gustavo, 1972-

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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…5.4 Experimental Results5.4.1 Sample parts; 5.4.2 Computation results; 5.4.3 Comparisons of constraint handling methods; 5.4.4 Algorithm implementation; 5.5 Summary; 6. Collaborative Computer-Aided Design -- State-of-the-Art; 6.1 Introduction; 6.2 Visualisation-based Collaborative Systems; 6.2.1 3D representations for Web applications; 6.2.2 System architectures and implementation strategies; 6.3 Co-design Collaborative Systems; 6.3.1 System architectures; 6.3.2 Design coordination and team management; 6.3.3 Optimised feature and assembly-based representations.…”
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Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow. by Ravichandiran, Sudharsan

Table of Contents: “…Solving the taxi problem using Q learningSARSA; Solving the taxi problem using SARSA; The difference between Q learning and SARSA; Summary; Questions; Further reading; Chapter 6: Multi-Armed Bandit Problem; The MAB problem; The epsilon-greedy policy; The softmax exploration algorithm; The upper confidence bound algorithm; The Thompson sampling algorithm; Applications of MAB; Identifying the right advertisement banner using MAB; Contextual bandits; Summary; Questions; Further reading; Chapter 7: Deep Learning Fundamentals; Artificial neurons; ANNs; Input layer; Hidden layer; Output layer.…”
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Remote Sensing of Energy Fluxes and Soil Moisture Content. by Petropoulos, George P.

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Enterprise artificial intelligence transformation : a playbook for the next generation of business and technology leaders by Haq, Rashed

Table of Contents: “…Types of Uses for Machine Learning -- Types of Machine Learning Algorithms -- Supervised, Unsupervised, and Semisupervised Learning -- Making Data More Useful -- Semantic Reasoning -- Applications of AI -- PART II Artificial Intelligence in the Enterprise -- Chapter 3 AI in E-Commerce and Retail -- Digital Advertising -- Marketing and Customer Acquisition -- Cross-Selling, Up-Selling, and Loyalty -- Business-to-Business Customer Intelligence -- Dynamic Pricing and Supply Chain Optimization -- Digital Assistants and Customer Engagement -- Chapter 4 AI in Financial Services -- Anti-Money Laundering.…”
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