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Produktbild: Machine Learning, Optimization, and Data Science
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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

Aus der Reihe Lecture Notes in Computer Science
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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.03.2025

Abbildungen

XX, 160 illus., 134 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Giuseppe Nicosia + weitere

Verlag

Springer

Seitenzahl

512

Maße (L/B/H)

23,5/15,5/2,9 cm

Gewicht

797 g

Sprache

Englisch

ISBN

978-3-031-82480-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

04.03.2025

Abbildungen

XX, 160 illus., 134 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

512

Maße (L/B/H)

23,5/15,5/2,9 cm

Gewicht

797 g

Sprache

Englisch

ISBN

978-3-031-82480-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Machine Learning, Optimization, and Data Science

  • .- 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.