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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 /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Machine learning, optimization, and data science/ edited by Giuseppe Nicosia ... [et al.].
    其他題名: 9th International Conference, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers.
    其他題名: LOD 2023
    其他作者: Nicosia, Giuseppe.
    團體作者: International Conference on Machine Learning, Optmization, and Data Science
    出版者: Cham :Springer Nature Switzerland : : 2024.,
    面頁冊數: xxii, 515 p. :ill. (some col.), digital ;24 cm.
    內容註: 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-- Bilevel Optimization by Conditional Bayesian Optimization -- Few-Shot Learning for Character Recognition in Persian Historical Documents -- ProVolOne ?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.
    Contained By: Springer Nature eBook
    標題: Machine learning - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-53969-5
    ISBN: 9783031539695
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