Machine learning, optimization, and ...
LOD (Conference) (2024 :)

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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 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: 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22-25, 2024 : revised selected papers.
    其他題名: LOD 2024
    其他作者: Nicosia, Giuseppe.
    團體作者: LOD (Conference)
    出版者: Cham :Springer Nature Switzerland : : 2025.,
    面頁冊數: xx, 512 p. :ill. (some col.), digital ;24 cm.
    內容註: 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.
    Contained By: Springer Nature eBook
    標題: Machine learning - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-82481-4
    ISBN: 9783031824814
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