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| Link zu diesem Datensatz | https://d-nb.info/1359143319 |
| Titel | Machine Learning and Principles and Practice of Knowledge Discovery in Databases : International Workshops of ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers, Part III / edited by Rosa Meo, Fabrizio Silvestri |
| Person(en) |
Meo, Rosa (Herausgeber) Silvestri, Fabrizio (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2025 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2025 |
| Umfang/Format | Online-Ressource, XXI, 585 p. 163 illus., 148 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-031-74632-1 Printed edition:: ISBN: 978-3-031-74634-5 |
| Inhalt | -- XAI-TS: Explainable AI for Time Series: Advances and Applications. -- Introducing the Attribution Stability Indicator: a Measure for Time Series XAI Attributions. -- LMFD: Latent Monotonic Feature Discovery. -- LinC: Explaining Time Series Clusterings with User-Provided Constraints. -- Explainable Long- and Short-term Pattern Detection in Projected Sequential Data. -- XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining. -- Matching the expert’s knowledge via a counterfactual-based feature importance measure. -- Explaining Fatigue in Runners Using Time Series Analysis on Wearable Sensor Data. -- Wave Top-k Random-d Family Search: How to Guide an Expert in a Structured Pattern Space. -- Diffusion-based Visual Counterfactual Explanations - Towards Systematic Quantitative Evaluation. -- Exploring gender bias in misclassification with clustering and local explanations. -- Are Generative-based Graph Counterfactual Explainers Worth It?. -- FIPER: a Visual-based Explanation Combining Rules and Feature Importance. -- Manipulation Risks in Explainable AI: The Implications of the Disagreement Problem. -- Using Graph Neural Networks for the Detection and Explanation of Network Intrusions. -- Game Theoretic Explanations for Graph Neural Networks. -- From Black Box to Glass Box: Evaluating the Faithfulness of Process Predictions with GCNNs. -- A New Class of Intelligible Models for Tabular Learning. -- Deep Learning for Sustainable Precision Agriculture. -- Plant Disease Detection using Deep Learning: A. -- Proof of Concept on Pear Leaf Disease Detection. -- Modelling Solar PV Adoption in Irish Dairy Farms using Agent-Based Modelling. -- Deep Networks based Approach for Automatic Counting Panicles on UAV captured Paddy RGB Imagery. -- The ACRE Crop-Weed Dataset for Benchmarking Weed Detection Models on Maize and Beans Fields. -- Integrating Renewable Energy in Agriculture: A Deep Reinforcement Learning-based Approach. -- Knowledge Guided Machine Learning. -- Unsupervised Ontology- and Taxonomy Construction through Hyperbolic Relational Domains and Ranges. -- A Filter-based Neural ODE Approach for Modelling Natural Systems with Prior Knowledge Constraints. -- Towards Automatically Refining Low-Quality Domain Knowledge: A Case Study in Healthcare. -- Lorentz-invariant augmentation for high-energy physics deep learning models. -- Discovering SpatioTemporal Warning Contexts from Non-Emergency Call Reports. -- SEEDOT: Tool for Enhancing Sentiment Lexicon with Machine Learning. -- MACLEAN: MAChine Learning for EArth ObservatioN. -- Detection and semantic description of changes in Earth Observation Time Series data. -- Low-rank hierarchical clustering of PRISMA hyperspectral images to identify burned areas. -- Next day fire prediction via semantic segmentation. -- Robust Burned Area Delineation through Multitask Learning. -- Burnt area extraction from high-resolution satellite images based on anomaly detection. -- Seasonal average temperature forecast with the AutoGluonTS modern autoML tool. -- MLG: Mining and Learning with Graphs. -- Curvature-based Pooling within Graph Neural Networks. -- Finding coherent node groups in directed graphs. -- Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences. -- Constructing Neural Forms for Hard-Constraint PINNs with Complex Dirichlet Boundaries. -- Enhancing generability: AutoML for robust denoising of strong gravitational lens systems. -- Data-Efficient Interactive Multi-Objective Optimization Using ParEGO. -- New Frontiers in Mining Complex Patterns. -- Striving for Simplicity in Deep Neural Models Trained for Malware Detection. -- On the Effectiveness of Non-negative Matrix Factorization for Text Open-set Recognition. -- Real-time Anomaly Prediction from Cryptocurrency Time Series. -- A Joint Analysis of Trajectory Mining and Process Mining for Smartphone User Behaviour. -- Towards Automation of Pollen Monitoring - Dealing with the Background in Pollen Monitoring Images |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2503090305598.450017132067 DOI: 10.1007/978-3-031-74633-8 |
| URL | https://doi.org/10.1007/978-3-031-74633-8 |
| ISBN/Einband/Preis | 978-3-031-74633-8 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Communications in Computer and Information Science ; 2135 |
| DDC-Notation | 006.31 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 004 Informatik |
| Online-Zugriff | Archivobjekt öffnen |
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