Machine Learning, Optimization, and Data Science: 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I

Author:   Giuseppe Nicosia ,  Varun Ojha ,  Emanuele La Malfa ,  Gabriele La Malfa
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2024
Volume:   14505
ISBN:  

9783031539688


Pages:   515
Publication Date:   16 February 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Machine Learning, Optimization, and Data Science: 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I


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Author:   Giuseppe Nicosia ,  Varun Ojha ,  Emanuele La Malfa ,  Gabriele La Malfa
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2024
Volume:   14505
Weight:   0.819kg
ISBN:  

9783031539688


ISBN 10:   3031539680
Pages:   515
Publication Date:   16 February 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

"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."

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