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Machine Learning, Optimization, and Big Data [[electronic resource] ] : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton
Machine Learning, Optimization, and Big Data [[electronic resource] ] : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (XXI, 600 p. 154 illus.)
Disciplina 006.31
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Application software
Artificial intelligence
Algorithms
Data mining
Computer science—Mathematics
Computer organization
Information Systems Applications (incl. Internet)
Artificial Intelligence
Algorithm Analysis and Problem Complexity
Data Mining and Knowledge Discovery
Mathematics of Computing
Computer Systems Organization and Communication Networks
ISBN 3-319-72926-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Cellular Networks -- 2.2 Modeling Approach -- 2.3 Framework Overview -- 3 Model Representation Format -- 4 From Reading to Model -- 4.1 Simple Interaction Translation -- 4.2 Translation of Translocation Interaction -- 4.3 Translation of Complexes -- 4.4 Translation of Nested Interactions -- 4.5 Translation of Direct and Indirect Interactions -- 4.6 Translation from Table Reading Output -- 5 Matching Reading and Modeling -- 5.1 Protein Families -- 5.2 Cell Type -- 5.3 Cellular Location -- 5.4 Contradicting Interaction Type -- 5.5 Negative Information -- 6 Case Study -- 7 Conclusion -- References -- Improving Support Vector Machines Performance Using Local Search -- 1 Introduction -- 2 Support Vector Machines -- 3 Iterated Local Search -- 4 Our ILS Method for SVM Parameters Tuning -- 5 Experimental Analysis -- 6 Conclusions and Future Research -- References -- Projective Approximation Based Quasi-Newton Methods -- 1 Introduction -- 2 Preliminaries -- 2.1 Notation Remarks -- 2.2 Quadratic Response Surface Methodology -- 2.3 Quasi-Newton Optimization Methods -- 3 Algorithm Descriptions -- 4 Theoretical Ground -- 5 Modelling -- 6 Conclusion -- A Proofs -- References -- Intra-feature Random Forest Clustering -- Abstract -- 1 Introduction -- 2 The Algorithm -- 3 Performance Evaluation -- 4 Conclusions -- References -- Dolphin Pod Optimization -- 1 Introduction -- 2 Dolphin Pod Optimization -- 3 DPO Setting Parameters -- 4 Performance Metrics -- 5 Numerical Results -- 5.1 Analytical Benchmark Functions -- 5.2 Hull-Form SBD Optimization Problem -- 6 Conclusions and Future Work -- References -- Contraction Clustering (RASTER) -- 1 Introduction -- 2 Problem Description.
2.1 The Clustering Problem -- 2.2 Motivating Use Case -- 2.3 Limitations of Common Clustering Methods -- 3 RASTER -- 3.1 High-Level Description -- 3.2 Tiles and RASTER Clusters -- 3.3 The Algorithm -- 3.4 Parallel RASTER -- 3.5 Generalizing to Higher Dimensions -- 3.6 Minimum Cluster Size in Disadvantageous Grid Layouts -- 4 Results -- 4.1 Ideal Data -- 4.2 Sample Datasets -- 4.3 Empirical Runtime -- 5 Related Work -- 6 Future Work -- References -- Deep Statistical Comparison Applied on Quality Indicators to Compare Multi-objective Stochastic Optimization Algorithms -- 1 Introduction -- 2 Related Work -- 3 Deep Statistical Comparison -- 4 Results and Discussion -- 4.1 Experimental Setup -- 4.2 First Experiment -- 4.3 Second Experiment -- 5 Conclusion -- References -- On the Explicit Use of Enzyme-Substrate Reactions in Metabolic Pathway Analysis -- 1 Introduction -- 1.1 A Nash Equilibrium Approach to Metabolic Pathways -- 1.2 Element Mass Balances and Charge Balancing -- 2 Explicitly Incorporating Enzyme-Substrate Reactions -- 2.1 Enzyme-Substrate Reactions -- 2.2 An Example of Binding and Unbinding Reactions -- 2.3 Multiple Minima from Protein Docking -- 2.4 A Multi-scale Methodology for Including Enzyme-Substrate Reactions -- 2.5 Enzyme Activity -- 3 Numerical Results -- 4 Conclusions -- References -- A Comparative Study on Term Weighting Schemes for Text Classification -- 1 Introduction -- 2 Text Classification -- 3 Classifiers -- 4 Results and Discussion -- 4.1 Experiments -- 4.2 Evaluation -- 4.3 Results -- 5 Conclusion -- References -- Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces -- 1 Introduction -- 2 Greedy Algorithms -- 3 Primal Convergence Results -- 4 Duality Gap and Convergence Result -- 5 Conclusion -- References -- Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization.
1 Introduction -- 2 Dimensionality Reduction Methods -- 2.1 General Definitions and Assumptions -- 2.2 Principal Component Analysis -- 2.3 Kernel Principal Component Analysis -- 2.4 Local Principal Component Analysis -- 2.5 Deep Autoencoders -- 3 Shape Modification of a Destroyer Hull -- 4 Numerical Results -- 4.1 Evaluation Metrics -- 4.2 Evaluation of Design-Space Dimensionality Reduction Capabilities -- 5 Conclusions and Future Work -- References -- A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner's Dilemma -- 1 Introduction -- 2 Differential Evolution: A Short Overview -- 3 Prisoner's Dilemma -- 3.1 Iterated PD and Benchmark Strategies -- 4 DE Develops IPD Strategies -- 4.1 The DE Approach with Memory -- 5 IPD Experiments -- 6 Conclusions -- References -- Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Training Set Creation -- 3.2 Classification -- 3.3 Dataset Pruning -- 4 Results -- 4.1 Test Set -- 4.2 Accuracy -- 5 Conclusion -- References -- Forecasting Natural Gas Flows in Large Networks -- 1 Introduction -- 1.1 Literature Review -- 1.2 The Data Set -- 1.3 Input Features -- 1.4 The Network -- 1.5 Evaluation -- 2 Recurrent Neural Network (RNN) with Design of Experiments (DOE) and Simulated Annealing -- 2.1 The Experiment -- 2.2 Optimal Design with Simulated Annealing -- 3 Recurrent Neural Network (RNN) with Genetic Algorithm (GA) -- 4 Conclusion -- References -- A Differential Evolution Algorithm to Semivectorial Bilevel Problems -- Abstract -- 1 Introduction -- 2 The SVBLP: Optimistic vs. Pessimistic Approaches -- 3 Optimistic and Pessimistic Frontiers -- 4 A Differential Evolution Algorithm for the SVBLP -- 5 Computational Experiment -- 6 Conclusions -- Acknowledgment -- References.
Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces -- 1 Introduction -- 2 Related Work on Transfer Learning in BCI -- 2.1 Ensembles -- 2.2 ELGI -- 3 Methodology -- 3.1 P300 Speller Paradigm -- 3.2 Dataset Recordings -- 3.3 Prefiltering -- 3.4 Classifier -- 3.5 Conditions -- 3.6 Compared Algorithms -- 4 Evolved ELGI Ensemble -- 5 Results -- 6 Discussion and Conclusion -- References -- Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm with Local Linesearch -- 1 Introduction -- 2 Optimization Problem Formulation -- 3 Performance Metrics -- 4 Hybrid Global/Local Deterministic Algorithm -- 4.1 MODPSO -- 4.2 DFMO -- 4.3 MODHA -- 4.4 Algorithm Parameters and Setup -- 5 Numerical Results -- 5.1 Analytical Benchmark Problems -- 5.2 High-Speed Catamaran Optimization -- 6 Conclusions and Future Work -- References -- Artificial Bee Colony Optimization to Reallocate Personnel to Tasks Improving Workplace Safety -- 1 Introduction -- 2 Multi-objective Optimization -- 2.1 Non-dominated Sorting Bee Colony Optimization -- 3 Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) -- 4 Worker's Risk Perception and Caution -- 5 Problem Formulation -- 5.1 Objectives -- 5.2 Problem Formulation -- 6 Experiments and Discussion -- 6.1 Dataset -- 6.2 Setup of the Parameters -- 6.3 Optimization Results -- 7 Conclusion -- References -- Multi-objective Genetic Algorithm for Interior Lighting Design -- 1 Introduction -- 2 The Inverse Lighting Problem -- 2.1 Blender as Direct Engine -- 3 Multi-objective Optimization -- 3.1 Previous Related Works -- 3.2 NSGA-II -- 3.3 Fitness Evaluation and Constraint Handling -- 4 The Proposed Strategy -- 5 Results -- 5.1 Art Gallery -- 5.2 Office -- 6 Conclusions -- References.
An Elementary Approach to the Problem of Column Selection in a Rectangular Matrix -- 1 Introduction -- 1.1 Historical Background -- 1.2 Our Contribution -- 2 Proof of Theorem 1.5 -- 2.1 Suitable Choice of the Extracted Vectors -- 2.2 Controlling the Individual Eigenvalues -- 2.3 Controlling the Greatest Eigenvalue -- 2.4 Two Simple Examples -- 3 Computational Considerations -- 3.1 A Simple Algorithm -- 3.2 Scalability vs Accuracy -- 3.3 Extracting Representative Images from a Dataset -- 4 Conclusion -- References -- A Simple and Effective Lagrangian-Based Combinatorial Algorithm for S3VMs -- 1 Introduction and Related Work -- 1.1 The Semi-supervised Scenario -- 1.2 Continuous vs Combinatorial Approach -- 2 Lagrangian S3VM -- 2.1 Dealing with Hyper-parameters -- 2.2 Balance Constraint as a Guide -- 2.3 Inductive vs Transductive S3VMs -- 2.4 Method Details -- 3 Experiments -- 3.1 Algorithms -- 3.2 Datasets -- 3.3 Model Selection -- 3.4 Experimental Results -- 3.5 Technical Details -- 4 Conclusion and Remarks -- References -- A Heuristic Based on Fuzzy Inference Systems for Multiobjective IMRT Treatment Planning -- Abstract -- 1 Introduction -- 2 Brief Review of the Literature -- 3 Multiobjective Optimization Problem -- 4 Heuristic Procedure Based on FIS -- 5 Illustration of the Application of the Procedure -- 6 Conclusions -- Acknowledgments -- References -- Data-Driven Machine Learning Approach for Predicting Missing Values in Large Data Sets: A Comparison ... -- Abstract -- 1 Introduction -- 2 Related Work -- 3 System Design -- 3.1 Data Source and Data Preparation -- 3.2 Methods for Imputation of Missing Values -- 4 Performance Measurements and Results -- 4.1 Algorithms Tuning -- 4.2 Evaluation Measures -- 4.3 Results and Considerations -- 5 Proposed Imputation Approach -- 6 Conclusions -- References.
Mineral: Multi-modal Network Representation Learning.
Record Nr. UNISA-996465494703316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning, Optimization, and Big Data : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton
Machine Learning, Optimization, and Big Data : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (XXI, 600 p. 154 illus.)
Disciplina 006.31
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Application software
Artificial intelligence
Algorithms
Data mining
Computer science - Mathematics
Computer engineering
Computer networks
Computer and Information Systems Applications
Artificial Intelligence
Data Mining and Knowledge Discovery
Mathematics of Computing
Computer Engineering and Networks
ISBN 9783319729268
3319729268
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Cellular Networks -- 2.2 Modeling Approach -- 2.3 Framework Overview -- 3 Model Representation Format -- 4 From Reading to Model -- 4.1 Simple Interaction Translation -- 4.2 Translation of Translocation Interaction -- 4.3 Translation of Complexes -- 4.4 Translation of Nested Interactions -- 4.5 Translation of Direct and Indirect Interactions -- 4.6 Translation from Table Reading Output -- 5 Matching Reading and Modeling -- 5.1 Protein Families -- 5.2 Cell Type -- 5.3 Cellular Location -- 5.4 Contradicting Interaction Type -- 5.5 Negative Information -- 6 Case Study -- 7 Conclusion -- References -- Improving Support Vector Machines Performance Using Local Search -- 1 Introduction -- 2 Support Vector Machines -- 3 Iterated Local Search -- 4 Our ILS Method for SVM Parameters Tuning -- 5 Experimental Analysis -- 6 Conclusions and Future Research -- References -- Projective Approximation Based Quasi-Newton Methods -- 1 Introduction -- 2 Preliminaries -- 2.1 Notation Remarks -- 2.2 Quadratic Response Surface Methodology -- 2.3 Quasi-Newton Optimization Methods -- 3 Algorithm Descriptions -- 4 Theoretical Ground -- 5 Modelling -- 6 Conclusion -- A Proofs -- References -- Intra-feature Random Forest Clustering -- Abstract -- 1 Introduction -- 2 The Algorithm -- 3 Performance Evaluation -- 4 Conclusions -- References -- Dolphin Pod Optimization -- 1 Introduction -- 2 Dolphin Pod Optimization -- 3 DPO Setting Parameters -- 4 Performance Metrics -- 5 Numerical Results -- 5.1 Analytical Benchmark Functions -- 5.2 Hull-Form SBD Optimization Problem -- 6 Conclusions and Future Work -- References -- Contraction Clustering (RASTER) -- 1 Introduction -- 2 Problem Description.
2.1 The Clustering Problem -- 2.2 Motivating Use Case -- 2.3 Limitations of Common Clustering Methods -- 3 RASTER -- 3.1 High-Level Description -- 3.2 Tiles and RASTER Clusters -- 3.3 The Algorithm -- 3.4 Parallel RASTER -- 3.5 Generalizing to Higher Dimensions -- 3.6 Minimum Cluster Size in Disadvantageous Grid Layouts -- 4 Results -- 4.1 Ideal Data -- 4.2 Sample Datasets -- 4.3 Empirical Runtime -- 5 Related Work -- 6 Future Work -- References -- Deep Statistical Comparison Applied on Quality Indicators to Compare Multi-objective Stochastic Optimization Algorithms -- 1 Introduction -- 2 Related Work -- 3 Deep Statistical Comparison -- 4 Results and Discussion -- 4.1 Experimental Setup -- 4.2 First Experiment -- 4.3 Second Experiment -- 5 Conclusion -- References -- On the Explicit Use of Enzyme-Substrate Reactions in Metabolic Pathway Analysis -- 1 Introduction -- 1.1 A Nash Equilibrium Approach to Metabolic Pathways -- 1.2 Element Mass Balances and Charge Balancing -- 2 Explicitly Incorporating Enzyme-Substrate Reactions -- 2.1 Enzyme-Substrate Reactions -- 2.2 An Example of Binding and Unbinding Reactions -- 2.3 Multiple Minima from Protein Docking -- 2.4 A Multi-scale Methodology for Including Enzyme-Substrate Reactions -- 2.5 Enzyme Activity -- 3 Numerical Results -- 4 Conclusions -- References -- A Comparative Study on Term Weighting Schemes for Text Classification -- 1 Introduction -- 2 Text Classification -- 3 Classifiers -- 4 Results and Discussion -- 4.1 Experiments -- 4.2 Evaluation -- 4.3 Results -- 5 Conclusion -- References -- Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces -- 1 Introduction -- 2 Greedy Algorithms -- 3 Primal Convergence Results -- 4 Duality Gap and Convergence Result -- 5 Conclusion -- References -- Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization.
1 Introduction -- 2 Dimensionality Reduction Methods -- 2.1 General Definitions and Assumptions -- 2.2 Principal Component Analysis -- 2.3 Kernel Principal Component Analysis -- 2.4 Local Principal Component Analysis -- 2.5 Deep Autoencoders -- 3 Shape Modification of a Destroyer Hull -- 4 Numerical Results -- 4.1 Evaluation Metrics -- 4.2 Evaluation of Design-Space Dimensionality Reduction Capabilities -- 5 Conclusions and Future Work -- References -- A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner's Dilemma -- 1 Introduction -- 2 Differential Evolution: A Short Overview -- 3 Prisoner's Dilemma -- 3.1 Iterated PD and Benchmark Strategies -- 4 DE Develops IPD Strategies -- 4.1 The DE Approach with Memory -- 5 IPD Experiments -- 6 Conclusions -- References -- Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Training Set Creation -- 3.2 Classification -- 3.3 Dataset Pruning -- 4 Results -- 4.1 Test Set -- 4.2 Accuracy -- 5 Conclusion -- References -- Forecasting Natural Gas Flows in Large Networks -- 1 Introduction -- 1.1 Literature Review -- 1.2 The Data Set -- 1.3 Input Features -- 1.4 The Network -- 1.5 Evaluation -- 2 Recurrent Neural Network (RNN) with Design of Experiments (DOE) and Simulated Annealing -- 2.1 The Experiment -- 2.2 Optimal Design with Simulated Annealing -- 3 Recurrent Neural Network (RNN) with Genetic Algorithm (GA) -- 4 Conclusion -- References -- A Differential Evolution Algorithm to Semivectorial Bilevel Problems -- Abstract -- 1 Introduction -- 2 The SVBLP: Optimistic vs. Pessimistic Approaches -- 3 Optimistic and Pessimistic Frontiers -- 4 A Differential Evolution Algorithm for the SVBLP -- 5 Computational Experiment -- 6 Conclusions -- Acknowledgment -- References.
Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces -- 1 Introduction -- 2 Related Work on Transfer Learning in BCI -- 2.1 Ensembles -- 2.2 ELGI -- 3 Methodology -- 3.1 P300 Speller Paradigm -- 3.2 Dataset Recordings -- 3.3 Prefiltering -- 3.4 Classifier -- 3.5 Conditions -- 3.6 Compared Algorithms -- 4 Evolved ELGI Ensemble -- 5 Results -- 6 Discussion and Conclusion -- References -- Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm with Local Linesearch -- 1 Introduction -- 2 Optimization Problem Formulation -- 3 Performance Metrics -- 4 Hybrid Global/Local Deterministic Algorithm -- 4.1 MODPSO -- 4.2 DFMO -- 4.3 MODHA -- 4.4 Algorithm Parameters and Setup -- 5 Numerical Results -- 5.1 Analytical Benchmark Problems -- 5.2 High-Speed Catamaran Optimization -- 6 Conclusions and Future Work -- References -- Artificial Bee Colony Optimization to Reallocate Personnel to Tasks Improving Workplace Safety -- 1 Introduction -- 2 Multi-objective Optimization -- 2.1 Non-dominated Sorting Bee Colony Optimization -- 3 Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) -- 4 Worker's Risk Perception and Caution -- 5 Problem Formulation -- 5.1 Objectives -- 5.2 Problem Formulation -- 6 Experiments and Discussion -- 6.1 Dataset -- 6.2 Setup of the Parameters -- 6.3 Optimization Results -- 7 Conclusion -- References -- Multi-objective Genetic Algorithm for Interior Lighting Design -- 1 Introduction -- 2 The Inverse Lighting Problem -- 2.1 Blender as Direct Engine -- 3 Multi-objective Optimization -- 3.1 Previous Related Works -- 3.2 NSGA-II -- 3.3 Fitness Evaluation and Constraint Handling -- 4 The Proposed Strategy -- 5 Results -- 5.1 Art Gallery -- 5.2 Office -- 6 Conclusions -- References.
An Elementary Approach to the Problem of Column Selection in a Rectangular Matrix -- 1 Introduction -- 1.1 Historical Background -- 1.2 Our Contribution -- 2 Proof of Theorem 1.5 -- 2.1 Suitable Choice of the Extracted Vectors -- 2.2 Controlling the Individual Eigenvalues -- 2.3 Controlling the Greatest Eigenvalue -- 2.4 Two Simple Examples -- 3 Computational Considerations -- 3.1 A Simple Algorithm -- 3.2 Scalability vs Accuracy -- 3.3 Extracting Representative Images from a Dataset -- 4 Conclusion -- References -- A Simple and Effective Lagrangian-Based Combinatorial Algorithm for S3VMs -- 1 Introduction and Related Work -- 1.1 The Semi-supervised Scenario -- 1.2 Continuous vs Combinatorial Approach -- 2 Lagrangian S3VM -- 2.1 Dealing with Hyper-parameters -- 2.2 Balance Constraint as a Guide -- 2.3 Inductive vs Transductive S3VMs -- 2.4 Method Details -- 3 Experiments -- 3.1 Algorithms -- 3.2 Datasets -- 3.3 Model Selection -- 3.4 Experimental Results -- 3.5 Technical Details -- 4 Conclusion and Remarks -- References -- A Heuristic Based on Fuzzy Inference Systems for Multiobjective IMRT Treatment Planning -- Abstract -- 1 Introduction -- 2 Brief Review of the Literature -- 3 Multiobjective Optimization Problem -- 4 Heuristic Procedure Based on FIS -- 5 Illustration of the Application of the Procedure -- 6 Conclusions -- Acknowledgments -- References -- Data-Driven Machine Learning Approach for Predicting Missing Values in Large Data Sets: A Comparison ... -- Abstract -- 1 Introduction -- 2 Related Work -- 3 System Design -- 3.1 Data Source and Data Preparation -- 3.2 Methods for Imputation of Missing Values -- 4 Performance Measurements and Results -- 4.1 Algorithms Tuning -- 4.2 Evaluation Measures -- 4.3 Results and Considerations -- 5 Proposed Imputation Approach -- 6 Conclusions -- References.
Mineral: Multi-modal Network Representation Learning.
Record Nr. UNINA-9910768197103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
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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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
Machine Learning, Optimization, and Data Science [[electronic resource] ] : 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I / / edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton
Machine Learning, Optimization, and Data Science [[electronic resource] ] : 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I / / edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton
Autore Nicosia Giuseppe
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (536 pages)
Disciplina 005.3
Altri autori (Persone) OjhaVarun
La MalfaEmanuele
La MalfaGabriele
PardalosPanos M
UmetonRenato
Collana Lecture Notes in Computer Science
Soggetto topico Information technology - Management
Computer networks
Electronic digital computers - Evaluation
Computer systems
Artificial intelligence
Machine learning
Computer Application in Administrative Data Processing
Computer Communication Networks
System Performance and Evaluation
Computer System Implementation
Artificial Intelligence
Machine Learning
ISBN 3-031-53969-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Consensus-based Participatory Budgeting for Legitimacy: Decision Support via Multi-agent Reinforcement Learning -- Leverage Mathematics? capability to compress and generalize as application of ML Embedding extraction from LLMs and its adaptation in the Automotive Space -- Speeding up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks -- 38 Flocking Method for Identifying of Neural Circuits in Optogenetic Datasets -- A Machine Learning Approach for Source Code Similarity via Graph-focused Features -- Knowledge distillation with Segment Anything (SAM) model for Planetary Geological Mapping -- ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation -- Perceptrons Under Veri able Random Data Corruption -- 104 Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach -- Solving Continuous Optimization Problems with a new Hyperheuristic Framework -- Benchmarking Named Entity Recognition Approaches for Extracting Research Infrastructure Information from Text -- Genetic Programming with Synthetic Data for Interpretable Regression Modelling and Limited Data -- A FastMap-Based Framework for E ciently Computing Top-K Projected Centrality -- Comparative analysis of machine learning models for time-series forecasting of Escherichia coli contamination in Portuguese shell sh production areas -- The Price of Data Processing Gail Gilboa Freedman -- Reward Shaping for Job Shop Scheduling -- A 3D Terrain Generator: Enhancing Robotics Simulations with GANs -- Hybrid Model for Impact Analysis of Climate Change on Droughts in Indian Region -- Bilevel Optimization by Conditional Bayesian Optimization -- Few-Shot Learning for Character Recognition in Persian Historical Documents -- ProVolOne ? Protein Volume Prediction Using a Multi-Attention, Multi-Resolution Deep Neural Network and Finite Element Analysis -- A data-driven monitoring approach for diagnosing quality degradation in a glass containerprocess -- Exploring emergent properties of recurrent neural networks using novel energy function formalism -- Co-Imagination of Behaviour & Morphology of Agents -- An Evolutionary Approach to Feature Selection and Classification -- "It Looks All the Same to Me": Cross-index Training for Long-term Financial Series Prediction -- U-FLEX: Unsupervised Feature Learning with Evolutionary eXploration -- Improved Filter-Based Feature Selection Techniques Based on Correlation and Clustering Techniques -- Deep Active Learning with Concept Drifts for detection of Mercury's Bow Shock and Magnetopause Crossings -- Modeling Primacy, Recency, and Cued recall in serial memory task using on-center o -surround recurrent neural network -- Joining Emission Data from Diverse Economical Activity Taxonomies with Evolution Strategies -- GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators -- Can Complexity Measures and Instance Hardness Measures Reflect the Actual Complexity of Microarray Data -- Two Steps Forward and One Behind: Rethinking Time Series Forecasting with Deep Learning -- Real-Time Emotion Recognition in Online Video Conferences for Medical Consultations -- Attentive perturbation: extending pre x tuning to large language models inner representations -- SoftCut: a fully di erentiable relaxed graph cut approach for deep learning image segmentation.
Record Nr. UNISA-996587861803316
Nicosia Giuseppe  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning, Optimization, and Data Science [[electronic resource] ] : 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton
Machine Learning, Optimization, and Data Science [[electronic resource] ] : 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton
Autore Nicosia Giuseppe
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (503 pages)
Disciplina 005.3
Altri autori (Persone) OjhaVarun
La MalfaEmanuele
La MalfaGabriele
PardalosPanos M
UmetonRenato
Collana Lecture Notes in Computer Science
Soggetto topico Information technology - Management
Computer networks
Electronic digital computers - Evaluation
Computer systems
Artificial intelligence
Machine learning
Computer Application in Administrative Data Processing
Computer Communication Networks
System Performance and Evaluation
Computer System Implementation
Artificial Intelligence
Machine Learning
ISBN 3-031-53966-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Integrated Human-AI Forecasting for Preventive Maintenance Task Duration Estimation -- Exploring Image Transformations with Diffusion Models: A Survey of Applications and Implementation Code -- Geolocation Risk Scores for Credit Scoring Models -- Social Media Analysis: The Relationship between Private Investors and Stock Price -- Deep learning model of two-phase fluid transport through fractured media: a real-world case study -- A Proximal Algorithm for Network Slimming -- Diversity in deep generative models and generative AI -- Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes -- kolopoly: Case Study on Large Action Spaces in Reinforcement Learning -- Alternating mixed-integer programming and neural network training for approximating stochastic two-stage problems -- Heaviest and densest subgraph computation for binary classification. A case study -- SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization -- Accelerated Graph Integration with Approximation of Combining Parameters -- Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non- Visual Environments: A Comparison -- A hybrid steady-state genetic algorithm for the minimum conflict spanning tree problem -- Reinforcement learning for multi-neighborhood local search in combinatorial optimization -- Evaluation of Selected Autoencoders in the Context of End-User Experience Management -- Application of multi-agent reinforcement learning to the dynamic scheduling problem in manufacturing systems -- Solving Mixed Influence Diagrams by Reinforcement Learning -- Multi-Scale Heat Kernel Graph Network for Graph Classification -- Accelerating Random Orthogonal Search for Global Optimization using Crossover -- A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application to Vehicles Emissions -- LSTM noise robustness: a case study for heavy vehicles -- Ensemble Clustering for Boundary Detection in High-Dimensional Data -- Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains -- Towards an Interpretable Functional Image-Based Classifier: Dimensionality -- Reduction of High-Density Di use Optical Tomography Data -- On Ensemble Learning for Mental Workload Classification -- Decision-making over compact preference structures -- User-Like Bots for Cognitive Automation: A Survey -- On Channel Selection for EEG-based Mental Workload Classification -- What Song Am I Thinking Of -- Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data -- Sensitivity Analysis for Feature Importance in Predicting Alzheimer?s Disease -- A Radically New Theory of how the Brain Represents and Computes with Probabilities.
Record Nr. UNISA-996587861903316
Nicosia Giuseppe  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui