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Titlebook: Machine Learning, Optimization, and Data Science; 7th International Co Giuseppe Nicosia,Varun Ojha,Renato Umeton Conference proceedings 202

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Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction, approaches in modeling of dynamical systems are the physical and the data-driven one. Both approaches are sufficient for a wide range of applications but suffer from various disadvantages, e.g., a reduced accuracy due to the limitations of the physical model or due to missing data. In this work, a
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KAFE: Knowledge and Frequency Adapted Embeddings,updates of each word vector. This makes word frequency a major factor in the quality of embedding, and in general the embedding of words with few training occurrences end up being of poor quality. This is problematic since rare and frequent words, albeit semantically similar, might end up far from e
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,A Hybrid Surrogate-Assisted Accelerated Random Search and Trust Region Approach for Constrained Blated Random Search (CARS-RBF) with the CONORBIT trust region method. Extensive numerical experiments have shown the effectiveness of the CARS-RBF and CONORBIT algorithms on many test problems and the hybrid algorithm combines the strengths of these methods. The proposed CARS-RBF-CONORBIT hybrid alter
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,A Large Visual Question Answering Dataset for Cultural Heritage, rely on Machine Learning algorithms that need to be trained on large annotated datasets. Once trained, a machine learning model is barely portable on a different domain. This calls for agile methodologies for building large annotated datasets from existing resources. The cultural heritage domain re
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,Zero-Shot Learning-Based Detection of Electric Insulators in the Wild,. Unmanned Aerial Vehicles (UAV’s) are used to inspect conditions of electric insulators placed in remote and hostile terrains where human inspection is not possible. Insulators vary in terms of physical appearance and hence the insulator detection technology present in the UAV in principle should b
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