Search Results - "fraud detection"

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    Big Data and Artificial Intelligence in Digital Finance Increasing Personalization and Trust in Digital Finance using Big Data and AI /

    Published 2022
    Table of Contents: “…Introduction -- Part I: Novel Big Data and AI Technologies for Digital Finance -- A Reference Architecture for Big Data Systems and AI Applications in the Finance Sector -- Hybrid Transactional and Analytical Processing for Integrated Data Management in Digital Finance and FinTech Applications -- Semantic Interoperability Modelling for Digital Finance Applications -- Semantic Streaming for Digital Finance Applications -- Part II: Blockchain Technologies and Digital Currencies for Digital Finance Applications -- Central Bank Digital Currencies and a Euro for the Future -- Efficient and Accelerated KYC Using Blockchain Technologies -- Part III: Applications of Big Data and AI in Digital Finance -- AI-based platform for Intelligent and Automated Accounting -- Addressing Intra-Day Volatility in Risk Assessments for Forex Trading -- Next-Generation Personalized Investment Recommendations -- Personalized Finance Management for Small Medium Businesses -- AML/CF supervision empowered by AI -- AnalyzingLarge Scale Blockchain Transaction Graphs for Fraudulent Activities -- Cybersecurity and Fraud Detection in Financial Transactions -- Part IV: Applications of Big Data and AI in Insurance -- Risk assessment for personalized health insurance products -- Alternative Data for Personalized Insurance products -- Part V: Technologies for Regulatory Compliance in the Finance Sector -- AI Governance -Trustworthy and Responsible use of AI -- Large Scale Data Anonymization for GDPR Compliance -- Conclusion.…”
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    Advances in Intelligent Data Analysis XVIII 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings /

    Published 2020
    Table of Contents: “…Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder -- Dual Sequential Variational Autoencoders for Fraud Detection -- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks -- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams -- GraphMDL: Graph Pattern Selection Based on Minimum Description Length -- Towards Content Sensitivity Analysis -- Gibbs Sampling Subjectively Interesting Tiles -- Even Faster Exact k-Means Clustering -- Ising-Based Consensus Clustering on Special Purpose Hardware -- Transfer Learning by Learning Projections from Target to Source -- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs -- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces -- Vouw: Geometric Pattern Mining Using the MDL Principle -- A Consensus Approach to Improve NMF Document Clustering -- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams -- Widening for MDL-Based Retail Signature Discovery -- Addressing the Resolution Limit and the Field of View Limit in Community Mining -- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics -- Adversarial Attacks Hidden in Plain Sight -- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code -- Overlapping Hierarchical Clustering (OHC) -- Digital Footprints of International Migration on Twitter -- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks -- A Late-Fusion Approach to Community Detection in Attributed Networks -- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction -- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization -- Actionable Subgroup Discovery and Urban Farm Optimization -- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model -- Detection ofDerivative Discontinuities in Observational Data -- Improving Prediction with Causal Probabilistic Variables -- DO-U-Net for Segmentation and Counting -- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media -- Event Recognition Based on Classification of Generated Image Captions -- Human-to-AI Coach: Improving Human Inputs to AI Systems -- Aleatoric and Epistemic Uncertainty with Random Forests -- Master your Metrics with Calibration -- Supervised Phrase-Boundary Embeddings -- Predicting Remaining Useful Life with Similarity-Based Priors -- Orometric Methods in Bounded Metric Data -- Interpretable Neuron Structuring with Graph Spectral Regularization -- Comparing the Preservation of Network Properties by Graph Embeddings -- Making Learners (More) Monotone -- Combining Machine Learning and Simulation to a Hybrid Modelling Approach -- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification -- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.…”
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