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Record Nr. |
UNINA9910983312803321 |
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Autore |
Meo Rosa |
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Titolo |
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 IV / / edited by Rosa Meo, Fabrizio Silvestri |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (513 pages) |
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Collana |
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Communications in Computer and Information Science, , 1865-0937 ; ; 2136 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Image processing - Digital techniques |
Computer vision |
Computer engineering |
Computer networks |
Application software |
Computers |
Data structures (Computer science) |
Information theory |
Artificial Intelligence |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Computer Engineering and Networks |
Computer and Information Systems Applications |
Computing Milieux |
Data Structures and Information Theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- PharML, Machine Learning for Pharma and Healthcare Applications. -- CORKI: A Correlation-driven Imputation Method for Partial Annotation Scenarios in Multi-Label Clinical Problems. -- Neuro-Symbolic Artificial Intelligence for Patient Monitoring. -- Direct One- |
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to-all Lead Conversion on 12-Lead Electrocardiogram. -- Unveiling Driver Modules in Lung Cancer: A Clustering-Based Gene-Gene Interaction Network Analysis. -- Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation. -- Predicting Sepsis Onset with Deep Federated Learning. -- A Workflow for Creating Multimodal Machine Learning Models for Metastasis Predictions in Melanoma Patients. -- Molecular Fingerprints-based Machine Learning. -- Simplification, Compression, Efficiency and Frugality for Artificial intelligence. -- Neural Networks comprising Sequentially Semiseparable Matrices with one dimensional State Variable are Universal Approximators. -- TinyMetaFed: Efficient Federated Meta-Learning for TinyML. -- On The Potentials of Input Repetition in CNN Networks for Reducing Multiplications. -- The Quest of Finding the Antidote to Sparse Double Descent. -- Unveiling the Potential of Tiny Machine Learning for Enhanced People Counting in UWB Radar Data. -- Towards Comparable Knowledge Distillation in Semantic Image Segmentation. -- Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers. -- Addressing limitations of TinyML approaches for AI-enabled Ambient Intelligence (Position Paper). -- Leveraging low rank filters for efficient and knowledge-preserving lifelong learning. -- Learning when to observe: A frugal reinforcement learning framework for a high-cost world. -- Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making. -- Exploiting causal knowledge during CATE estimation using tree based metalearners. -- A Parameter-Free Bayesian Framework for Uplift Modeling - Application on Telecom Data. -- A churn prediction dataset from the telecom sector: a new benchmark for uplift modeling. -- 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL) . -- Semi-Supervised Co-Teaching for Monitoring Parkinson's Disease Patients. -- Explainable Artificial Intelligence in Medical Diagnostics: Insights into Alzheimer's Disease. -- Cross-Modal Video to Body-joints Augmentation for Rehabilitation Exercise Quality Assessment. -- Multimodal Sensor Fusion for Daily Living Activities Recognition in Active Assisted Living for Older Adults. -- Modeling and Detecting Urinary Anomalies in Seniors from Data obtained by Unintrusive Sensors. -- Assessing Frailty Using Behavioral and Physical Health Data in Everyday Living Settings. -- Synthesizing Diabetic Foot Ulcer Images with Diffusion Model. -- Engaging Older Adults at Meal-time through AI-empowered Socially Assistive Robots. -- Investigating the Dynamics of Cardio-metabolic Comorbidities and their Interactions in Ageing Adults through Dynamic Bayesian Networks. -- Adapting to Change: Reliable Multimodal Learning Across Domains. -- Harnessing Error Patterns to Estimate Out-Of-Distribution Performance. -- HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues. -- CAD Models to Real-World Images: A Practical Approach to Unsupervised Domain Adaptation in Industrial Object Classification. -- EMG subspace alignment and visualization for cross-subject hand gesture classification. -- Adapting Classifiers To Changing Class Priors During Deployment. -- AI4M: AI for Manufacturing. -- Applying Machine Learning Models on Metrology Data for Predicting Device Electrical Performance. -- Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply Chains. -- Reinforcement Learning for Segmented Manufacturing. -- Automatic tool wear inspection by cascading sensor and image data. |
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Sommario/riassunto |
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The five-volume set CCIS 2133-2137 constitutes the refereed proceedings of the workshops held in conjunction with the Joint European Conference on Machine Learning and Knowledge Discovery in |
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Databases, ECML PKDD 2023, which took place in Turin, Italy, during September 18-22, 2023. The 200 full papers presented in these proceedings were carefully reviewed and selected from 515 submissions. The papers have been organized in the following tracks: Part I: Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial; BIAS 2023 - 3rd Workshop on Bias and Fairness in AI; Biased Data in Conversational Agents; Explainable Artificial Intelligence: From Static to Dynamic; ML, Law and Society; Part II: RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education; SoGood 2023 – 8th Workshop on Data Science for Social Good; Towards Hybrid Human-Machine Learning and Decision Making (HLDM); Uncertainty meets explainability in machine learning; Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation; Part III: XAI-TS: Explainable AI for Time Series: Advances and Applications; XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining; Deep Learning for Sustainable Precision Agriculture; Knowledge Guided Machine Learning; MACLEAN: MAChine Learning for EArth ObservatioN; MLG: Mining and Learning with Graphs; Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences; New Frontiers in Mining Complex Patterns; Part IV: PharML, Machine Learning for Pharma and Healthcare Applications; Simplification, Compression, Efficiency and Frugality for Artificial intelligence; Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making; 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL); Adapting to Change: Reliable Multimodal Learning Across Domains; AI4M: AI for Manufacturing; Part V: Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications; Deep learning meets Neuromorphic Hardware; Discovery challenge; ITEM: IoT, Edge, and Mobile for Embedded Machine Learning; LIMBO - LearnIng and Mining for BlOckchains; Machine Learning for Cybersecurity (MLCS 2023); MIDAS - The 8th Workshop on MIning DAta for financial applicationS; Workshop on Advancements in Federated Learning. |
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