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Foundation Models for Natural Language Processing [[electronic resource] ] : Pre-trained Language Models Integrating Media / / by Gerhard Paass, Sven Giesselbach
| Foundation Models for Natural Language Processing [[electronic resource] ] : Pre-trained Language Models Integrating Media / / by Gerhard Paass, Sven Giesselbach |
| Autore | Paass Gerhard |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (xviii, 448 pages) |
| Disciplina | 006.35 |
| Collana | Artificial Intelligence: Foundations, Theory, and Algorithms |
| Soggetto topico |
Natural language processing (Computer science)
Computational linguistics Artificial intelligence Expert systems (Computer science) Machine learning Natural Language Processing (NLP) Computational Linguistics Artificial Intelligence Knowledge Based Systems Machine Learning |
| ISBN | 9783-031-23190-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. Pre-trained Language Models -- 3. Improving Pre-trained Language Models -- 4. Knowledge Acquired by Foundation Models -- 5. Foundation Models for Information Extraction -- 6. Foundation Models for Text Generation -- 7. Foundation Models for Speech, Images, Videos, and Control -- 8. Summary and Outlook. |
| Record Nr. | UNINA-9910725929703321 |
Paass Gerhard
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Foundation Models for Natural Language Processing [[electronic resource] ] : Pre-trained Language Models Integrating Media / / by Gerhard Paass, Sven Giesselbach
| Foundation Models for Natural Language Processing [[electronic resource] ] : Pre-trained Language Models Integrating Media / / by Gerhard Paass, Sven Giesselbach |
| Autore | Paass Gerhard |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (xviii, 448 pages) |
| Disciplina | 006.35 |
| Collana | Artificial Intelligence: Foundations, Theory, and Algorithms |
| Soggetto topico |
Natural language processing (Computer science)
Computational linguistics Artificial intelligence Expert systems (Computer science) Machine learning Natural Language Processing (NLP) Computational Linguistics Artificial Intelligence Knowledge Based Systems Machine Learning |
| ISBN | 9783-031-23190-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. Pre-trained Language Models -- 3. Improving Pre-trained Language Models -- 4. Knowledge Acquired by Foundation Models -- 5. Foundation Models for Information Extraction -- 6. Foundation Models for Text Generation -- 7. Foundation Models for Speech, Images, Videos, and Control -- 8. Summary and Outlook. |
| Record Nr. | UNISA-996547972703316 |
|
Paass Gerhard
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Foundation Models for Natural Language Processing : Pre-trained Language Models Integrating Media / / Gerhard Paaß , Sven Giesselbach
| Foundation Models for Natural Language Processing : Pre-trained Language Models Integrating Media / / Gerhard Paaß , Sven Giesselbach |
| Autore | Paass Gerhard |
| Pubbl/distr/stampa | Springer International Publishing, 2023 |
| Altri autori (Persone) | GiesselbachSven |
| ISBN | 3-031-23190-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996591072603316 |
|
Paass Gerhard
|
||
| Springer International Publishing, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Foundation Models for Natural Language Processing : Pre-trained Language Models Integrating Media / / by Gerhard Paaß, Sven Giesselbach
| Foundation Models for Natural Language Processing : Pre-trained Language Models Integrating Media / / by Gerhard Paaß, Sven Giesselbach |
| Autore | Paaß Gerhard |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource |
| Disciplina | 006.35 |
| Altri autori (Persone) | GiesselbachSven |
| Collana | Artificial Intelligence: Foundations, Theory, and Algorithms |
| Soggetto topico |
Natural language processing (Computer science)
Computational linguistics Artificial intelligence Expert systems (Computer science) Machine learning Natural Language Processing (NLP) Computational Linguistics Artificial Intelligence Knowledge Based Systems Machine Learning |
| ISBN |
9783031231902
3031231902 |
| Classificazione | COM004000COM025000COM073000LAN009000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. Pre-trained Language Models -- 3. Improving Pre-trained Language Models -- 4. Knowledge Acquired by Foundation Models -- 5. Foundation Models for Information Extraction -- 6. Foundation Models for Text Generation -- 7. Foundation Models for Speech, Images, Videos, and Control -- 8. Summary and Outlook. |
| Record Nr. | UNINA-9910847154703321 |
|
Paaß Gerhard
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part III / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton
| Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part III / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton |
| Autore | Nicosia Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (425 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OjhaVarun
GiesselbachSven PardalosM. Panos UmetonRenato |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN |
9783031824876
9783031824869 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Combining EEG oscillation analysis and explainable artificial intelligence for characterizing visuospatial attention. -- Fully automatic meningioma segmentation with nnUNet using T1-weighted contrast-enhanced MR images by leveraging publicly available data and different types of annotations. -- Multimodal Shannon Game with Images. -- On the Role of Activation Functions in EEG-To-Text Decoder. -- INVISIONS: Innovative Neuromorphic Vision Sensors in real-scenarios. -- Path-weight-based Pruning and SHAP-based Explanations of an ANN with fMRI Data. -- Deep learning in a bilateral brain with hemispheric specialisation. -- A compact convolutional neural network for decoding EEG functional connectivity: application to motor imagery. -- Inference of Abstraction for Human-like Probabilistic Reasoning. -- Conformal Prediction for Uncertainty Quantification in Brain Age Estimation using Random Forests Quantile Regression on MRI Features of the HCP Young Adult. -- Emotional Reactions To AI-generated Images: A Pilot Study Using Neuro physiological Measures. -- Exploring Deep Learning Models for EEG Neural Decoding. -- Transfer Learning for the Cognitive Staging Prediction in Alzheimer’s Disease. -- Inference of Abstraction for Human-like Logical Reasoning. -- Sequence Learning with Analog Neuromorphic Multi-Compartment Neurons and On-Chip Structural STDP. -- Understanding Sleep Dynamics Gathered from Wearable Devices with Ex plainable Recurrent Neural Networks. -- Brain morphometry differences across sexes revealed through Explainable Artificial Intelligence: a Human Connectome Project Young Adult study. -- Left/Right brain, human motor control and the implications for robotics. -- Predicting Psychological Well-being in HCP Young Adult Cohort using Ran dom Forests Regression and SHAP with NIHTB Emotion Battery. |
| Record Nr. | UNINA-9910984691403321 |
|
Nicosia Giuseppe
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part I / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton
| Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part I / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton |
| Autore | Nicosia Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (826 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OjhaVarun
GiesselbachSven PardalosM. Panos UmetonRenato |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN |
9783031824814
9783031824807 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Solving Two-Stage Stochastic Programming problems via Machine Learning. -- Weight-varying Model Predictive Control for Coupled Cyber-Physical Systems: Aerial Grasping Study. -- Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach. -- Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services. -- Protein Sequence Generation using Denoising Probabilistic Diffusion Model. -- Individual Fairness in Generative Text Models. -- Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs. -- Artificial Intelligence and Cyber Security. -- Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis. -- Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading. -- Optimal risk scores for continuous predictors. -- Post-Treatment Gait Prediction after Botulinum Toxin Injections Using Deep Learning with an Attention Mechanism. -- Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Prediction. -- Nearest Neighbors Counterfactuals. -- An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning. -- Pattern detection in abnormal district heating data. -- Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs. -- Learn to Create Neighborhoods in Real-World Vehicle Routing Problem. -- PointerKex: A Pointer-based SSH Key Extraction method. -- Addressing The Permutation Flowshop Scheduling with Grey Wolf Optimizer. -- MCGRAN: Multi-Conditional Graph Generation for Neural Architecture Search. -- Generative reward machine for Reinforcement learning for Physical Internet Distribution Centre. -- Between accurate prediction and poor decision making: the AI/ML gap. -- Cross-Metapath based Hashing for Recommendation Systems. -- Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees. -- Augmented Human-AI Forecasting for Ship Refit Project Scheduling: A Predict-then-Optimize Approach. -- Evaluation of Document Deduplication Algorithms for Large Text Corpora. -- Hicks Traverse meets One-Factor SVM: Belief Incoherence Attractors. -- Synthetic Time Series for Anomaly Detection in Cloud Microservices. -- Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement Learning Approach. -- Leap: Inductive Link Prediction via Learnable Topology Augmentation. -- Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches. -- Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines. -- Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents. |
| Record Nr. | UNINA-9910984687903321 |
|
Nicosia Giuseppe
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton
| Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton |
| Autore | Nicosia Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (606 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OjhaVarun
GiesselbachSven PardalosM. Panos UmetonRenato |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN |
9783031824845
9783031824838 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Exploring Explainable Machine Learning for Enhanced Ship Performance Monitoring. -- Identifying Potential Key Point of Sale Customers Using Network Centrality. -- Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning. -- Predicting Multiple Sclerosis Worsening Using Stratification Based and Time Dependent Variables Extracted from Routine Visits Data. -- Predicting University Dropout Rates Using Machine Learning: UniCt case. -- Investigating on Gradient Regularization for Testing Neural Networks. -- SKIE SRL: Structured Key Information Extraction from Business Documents using Statistical Relational Learning. -- Leveraging LLM powered Systems to Accelerate Mycobacterium tuberculosis Research Step One: From Documents to the Vectorstore. -- Vegvisir: Probabilistic model (VAE) for viral T cell epitope prediction. -- Tiny Long Short Term Memory Model for Resource Constrained Prediction of Battery Cycle Life. -- Compact Artificial Neural Network Models for Predicting Protein Residue RNA Base Binding. -- FWin transformer for dengue prediction under climate and ocean influence. -- ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures. -- Topological Layering of Mouse Brain Activity in Light Sheet Microscopy Datasets. -- A Constraint Based Savings Algorithm for the Traveling Salesman Problem. -- Gaussian process interpolation with conformal prediction: methods and comparative analysis. -- Using embeddings of pre trained models for cross database dysarthria detection: supervised vs. self supervised approach. -- Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes. -- Integrating Logit Space Embeddings for Reliable Out of Distribution Detection. -- A Computational Framework for Identifying Salient Moments in Motion Capture Data. -- Machine Learning for the Evaluation of the Nephrops Norvegicus Population. -- Enhancing Cluster Based Topic Models through Parametric Dimensionality Reduction with Transformer Encoders. -- Enhancing Arrhythmia Detection Using an Ensemble of Transformer Models for Heartbeat Classification. -- Rapidly Computing Approximate Graph Convex Hulls via FastMap. -- Deep Gaussian mixture model for unsupervised image segmentation. -- Address Classification in E commerce Logistics Using Federated Learning. |
| Record Nr. | UNINA-9910984575703321 |
|
Nicosia Giuseppe
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part III / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton
| Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part III / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton |
| Autore | Nicosia Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (425 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OjhaVarun
GiesselbachSven PardalosM. Panos UmetonRenato |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN |
9783031824876
9783031824869 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Combining EEG oscillation analysis and explainable artificial intelligence for characterizing visuospatial attention. -- Fully automatic meningioma segmentation with nnUNet using T1-weighted contrast-enhanced MR images by leveraging publicly available data and different types of annotations. -- Multimodal Shannon Game with Images. -- On the Role of Activation Functions in EEG-To-Text Decoder. -- INVISIONS: Innovative Neuromorphic Vision Sensors in real-scenarios. -- Path-weight-based Pruning and SHAP-based Explanations of an ANN with fMRI Data. -- Deep learning in a bilateral brain with hemispheric specialisation. -- A compact convolutional neural network for decoding EEG functional connectivity: application to motor imagery. -- Inference of Abstraction for Human-like Probabilistic Reasoning. -- Conformal Prediction for Uncertainty Quantification in Brain Age Estimation using Random Forests Quantile Regression on MRI Features of the HCP Young Adult. -- Emotional Reactions To AI-generated Images: A Pilot Study Using Neuro physiological Measures. -- Exploring Deep Learning Models for EEG Neural Decoding. -- Transfer Learning for the Cognitive Staging Prediction in Alzheimer’s Disease. -- Inference of Abstraction for Human-like Logical Reasoning. -- Sequence Learning with Analog Neuromorphic Multi-Compartment Neurons and On-Chip Structural STDP. -- Understanding Sleep Dynamics Gathered from Wearable Devices with Ex plainable Recurrent Neural Networks. -- Brain morphometry differences across sexes revealed through Explainable Artificial Intelligence: a Human Connectome Project Young Adult study. -- Left/Right brain, human motor control and the implications for robotics. -- Predicting Psychological Well-being in HCP Young Adult Cohort using Ran dom Forests Regression and SHAP with NIHTB Emotion Battery. |
| Record Nr. | UNISA-996647969903316 |
|
Nicosia Giuseppe
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton
| Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton |
| Autore | Nicosia Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (606 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OjhaVarun
GiesselbachSven PardalosM. Panos UmetonRenato |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN |
9783031824845
9783031824838 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Exploring Explainable Machine Learning for Enhanced Ship Performance Monitoring. -- Identifying Potential Key Point of Sale Customers Using Network Centrality. -- Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning. -- Predicting Multiple Sclerosis Worsening Using Stratification Based and Time Dependent Variables Extracted from Routine Visits Data. -- Predicting University Dropout Rates Using Machine Learning: UniCt case. -- Investigating on Gradient Regularization for Testing Neural Networks. -- SKIE SRL: Structured Key Information Extraction from Business Documents using Statistical Relational Learning. -- Leveraging LLM powered Systems to Accelerate Mycobacterium tuberculosis Research Step One: From Documents to the Vectorstore. -- Vegvisir: Probabilistic model (VAE) for viral T cell epitope prediction. -- Tiny Long Short Term Memory Model for Resource Constrained Prediction of Battery Cycle Life. -- Compact Artificial Neural Network Models for Predicting Protein Residue RNA Base Binding. -- FWin transformer for dengue prediction under climate and ocean influence. -- ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures. -- Topological Layering of Mouse Brain Activity in Light Sheet Microscopy Datasets. -- A Constraint Based Savings Algorithm for the Traveling Salesman Problem. -- Gaussian process interpolation with conformal prediction: methods and comparative analysis. -- Using embeddings of pre trained models for cross database dysarthria detection: supervised vs. self supervised approach. -- Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes. -- Integrating Logit Space Embeddings for Reliable Out of Distribution Detection. -- A Computational Framework for Identifying Salient Moments in Motion Capture Data. -- Machine Learning for the Evaluation of the Nephrops Norvegicus Population. -- Enhancing Cluster Based Topic Models through Parametric Dimensionality Reduction with Transformer Encoders. -- Enhancing Arrhythmia Detection Using an Ensemble of Transformer Models for Heartbeat Classification. -- Rapidly Computing Approximate Graph Convex Hulls via FastMap. -- Deep Gaussian mixture model for unsupervised image segmentation. -- Address Classification in E commerce Logistics Using Federated Learning. |
| Record Nr. | UNISA-996647969703316 |
|
Nicosia Giuseppe
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part I / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton
| Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part I / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton |
| Autore | Nicosia Giuseppe |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (826 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
OjhaVarun
GiesselbachSven PardalosM. Panos UmetonRenato |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN |
9783031824814
9783031824807 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Solving Two-Stage Stochastic Programming problems via Machine Learning. -- Weight-varying Model Predictive Control for Coupled Cyber-Physical Systems: Aerial Grasping Study. -- Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach. -- Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services. -- Protein Sequence Generation using Denoising Probabilistic Diffusion Model. -- Individual Fairness in Generative Text Models. -- Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs. -- Artificial Intelligence and Cyber Security. -- Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis. -- Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading. -- Optimal risk scores for continuous predictors. -- Post-Treatment Gait Prediction after Botulinum Toxin Injections Using Deep Learning with an Attention Mechanism. -- Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Prediction. -- Nearest Neighbors Counterfactuals. -- An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning. -- Pattern detection in abnormal district heating data. -- Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs. -- Learn to Create Neighborhoods in Real-World Vehicle Routing Problem. -- PointerKex: A Pointer-based SSH Key Extraction method. -- Addressing The Permutation Flowshop Scheduling with Grey Wolf Optimizer. -- MCGRAN: Multi-Conditional Graph Generation for Neural Architecture Search. -- Generative reward machine for Reinforcement learning for Physical Internet Distribution Centre. -- Between accurate prediction and poor decision making: the AI/ML gap. -- Cross-Metapath based Hashing for Recommendation Systems. -- Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees. -- Augmented Human-AI Forecasting for Ship Refit Project Scheduling: A Predict-then-Optimize Approach. -- Evaluation of Document Deduplication Algorithms for Large Text Corpora. -- Hicks Traverse meets One-Factor SVM: Belief Incoherence Attractors. -- Synthetic Time Series for Anomaly Detection in Cloud Microservices. -- Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement Learning Approach. -- Leap: Inductive Link Prediction via Learnable Topology Augmentation. -- Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches. -- Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines. -- Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents. |
| Record Nr. | UNISA-996647970103316 |
|
Nicosia Giuseppe
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||