Search Results - (((((((want OR fine) OR semantic) OR carter) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

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    Pathway modeling and algorithm research

    Published 2011
    Table of Contents: “…PATHWAY MODELING AND ALGORITHM RESEARCH; PATHWAY MODELING AND ALGORITHM RESEARCH; Contents; Preface; Biological Pathways and Their Modeling; Abstract; 1. …”
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    An Introduction to Algorithmic Trading : Basic to Advanced Strategies. by Leshik, Edward, Cralle, Jane

    Published 2011
    Table of Contents: “…Introduction to trading algorithms. History ; All about trading algorithms you ever wanted to know ... ; Algos defined and explained ; Who uses and provides algos ; Why have they become mainstream so quickly? …”
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    Responsible Data Science : transparency and fairness in algorithms by Fleming, Grant

    Published 2021
    Table of Contents: “…Black-Box Models 35 -- Ethical Challenges with Interpretable Models 38 -- Black-Box Models 39 -- Ensembles 39 -- Nearest Neighbors 41 -- Clustering 41 -- Association Rules 42 -- Collaborative Filters 42 -- Artificial Neural Nets and Deep Neural Nets 43 -- Problems with Black-Box Predictive Models 45 -- Problems with Unsupervised Algorithms 47 -- Summary 48 -- Chapter 3 The Ways AI Goes Wrong, and the Legal Implications 49 -- AI and Intentional Consequences by Design 50 -- Deepfakes 50 -- Supporting State Surveillance and Suppression 51 -- Behavioral Manipulation 52 -- Automated Testing to Fine-Tune Targeting 53 -- AI and Unintended Consequences 55 -- Healthcare 56 -- Finance 57 -- Law Enforcement 58 -- Technology 60 -- The Legal and Regulatory Landscape around AI 61 -- Ignorance Is No Defense: AI in the Context of Existing Law and Policy 63 -- A Finger in the Dam: Data Rights, Data Privacy, and Consumer Protection Regulations 64 -- Trends in Emerging Law and Policy Related to AI 66 -- Summary 69 --…”
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    Semantic matchmaking with nonmonotonic description logics by Grimm, Stephan

    Published 2009
    Table of Contents: “…Nonmonotonic Reasoning in the Semantic WebNonmonotonic Description Logics; Autoepistemic Description Logics; Formal Semantics for Autoepistemic DLs; Reasoning with Epistemic Operators; Circumscriptive Description Logics; Formal Semantics for Circumscriptive DLs; Reasoning with Circumscribed Knowledge Bases; Terminological Defaults; Discussion; A Reasoning Algorithm for Circumscriptive Description Logics; Principle Idea of a Tableaux Extension; Extending DL Tableaux Calculi by Preference Clashes; Restrictions on the Formalism; Deciding Circumscriptive ALCO…”
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    Genetic Algorithms + Data Structures = Evolution Programs by Michalewicz, Zbigniew

    Published 1994
    Table of Contents: “…I. Genetic Algorithms -- 1 GAs: What Are They? -- 2 GAs: How Do They Work? …”
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    Graph algorithms and applications 3

    Published 2004
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    Data management in the semantic web

    Published 2011
    Table of Contents: “…DATA MANAGEMENT IN THE SEMANTIC WEB ; DATA MANAGEMENT IN THE SEMANTIC WEB ; CONTENTS ; PREFACE ; INTERPRETATIONS OF THE WEB OF DATA; Abstract; 1. …”
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    Learning OWL class expressions by Lehmann, Jens, 1982-

    Published 2010
    Table of Contents: “…Refinement Operator Based OWL Learning Algorithms; OCEL (OWL Class Expression Learner); Redundancy Elimination; Creating a Full Learning Algorithm; ELTL (EL Tree Learner)…”
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    Learning Neo4j 3.x - Second Edition. by Baton, Jerome

    Published 2017
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    Deep Learning for the Earth Sciences : A Comprehensive Approach to Remote Sensing, Climate Science and Geosciences. by Camps-Valls, Gustau

    Published 2021
    Table of Contents: “…6.1.4 Evaluation Metrics -- 6.1.4.1 Precision-Recall Curve -- 6.1.4.2 Average Precision and Mean Average Precision -- 6.1.5 Applications -- 6.2 Preliminaries on Object Detection with Deep Models -- 6.2.1 Two-stage Algorithms -- 6.2.1.1 R-CNNs -- 6.2.1.2 R-FCN -- 6.2.2 One-stage Algorithms -- 6.2.2.1 YOLO -- 6.2.2.2 SSD -- 6.3 Object Detection in Optical RS Images -- 6.3.1 Related Works -- 6.3.1.1 Scale Variance -- 6.3.1.2 Orientation Variance -- 6.3.1.3 Oriented Object Detection -- 6.3.1.4 Detecting in Large-size Images -- 6.3.2 Datasets and Benchmark -- 6.3.2.1 DOTA -- 6.3.2.2 VisDrone…”
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