Cover Image

On Vessel Location Forecasting and the Effect of Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tritsarolis, Andreas, Pelekis, Nikos, Bereta, Konstantina, Zissis, Dimitris, Theodoridis, Yannis
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning
by: Tritsarolis, Andreas, et al.
Published: (2026)

Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting
by: Tziorvas, Antonios, et al.
Published: (2026)

FLP-XR: Future Location Prediction on Extreme Scale Maritime Data in Real-time
by: Theodoropoulos, George S., et al.
Published: (2025)

Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
by: Kyriakopoulos, Iason, et al.
Published: (2025)

MoDE-Boost: Boosting Shared Mobility Demand with Edge-Ready Prediction Models
by: Tziorvas, Antonios, et al.
Published: (2026)

Towards Data-driven Nitrogen Estimation in Wheat Fields using Multispectral Images
by: Tritsarolis, Andreas, et al.
Published: (2026)

Efficient Deterministic Renewable Energy Forecasting Guided by Multiple-Location Weather Data
by: Symeonidis, Charalampos, et al.
Published: (2024)

Video Reconstruction using Diffusion-based Image-to-Video Generation with Trajectory Guidance
by: Bompai, Stelio, et al.
Published: (2026)

A Typed Tensor Language for Federated Learning
by: Mailis, Theofilos, et al.
Published: (2026)

A Trustworthy By Design Classification Model for Building Energy Retrofit Decision Support
by: Rempi, Panagiota, et al.
Published: (2025)

A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning
by: Malekzadeh, Parvin, et al.
Published: (2024)

DeepTSF: Codeless machine learning operations for time series forecasting
by: Pelekis, Sotiris, et al.
Published: (2023)

AI4EF: Artificial Intelligence for Energy Efficiency in the Building Sector
by: Tzortzis, Alexandros Menelaos, et al.
Published: (2024)

Data-driven building energy efficiency prediction using physics-informed neural networks
by: Michalakopoulos, Vasilis, et al.
Published: (2023)

Deriving Hematological Disease Classes Using Fuzzy Logic and Expert Knowledge: A Comprehensive Machine Learning Approach with CBC Parameters
by: Ameen, Salem, et al.
Published: (2024)

Trustworthy artificial intelligence in the energy sector: Landscape analysis and evaluation framework
by: Pelekis, Sotiris, et al.
Published: (2024)

Context-Enriched Natural Language Descriptions of Vessel Trajectories
by: Patroumpas, Kostas, et al.
Published: (2026)

Data-Driven Trajectory Imputation for Vessel Mobility Analysis
by: Spiliopoulos, Giannis, et al.
Published: (2026)

Transformer-Based Decomposition of Electrodermal Activity for Real-World Mental Health Applications
by: Tsirmpas, Charalampos, et al.
Published: (2025)

Federated Learning for Financial Forecasting
by: Noseda, Manuel, et al.
Published: (2025)

Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
by: Papageorgiou, Yiannis, et al.
Published: (2026)

EnvClus*: Extracting Common Pathways for Effective Vessel Trajectory Forecasting
by: Zygouras, Nikolaos, et al.
Published: (2024)

Environment-Aware Satellite Image Generation with Diffusion Models
by: Kostagiolas, Nikos, et al.
Published: (2025)

Colliding with Adversaries at ECML-PKDD 2025 Model Robustness Competition 1st Prize Solution
by: Stefanopoulos, Dimitris, et al.
Published: (2025)

EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning
by: Malekzadeh, Parvin, et al.
Published: (2024)

Federated Dynamic Modeling and Learning for Spatiotemporal Data Forecasting
by: Pham, Thien, et al.
Published: (2025)

Improved Bounds for Online Facility Location with Predictions
by: Fotakis, Dimitris, et al.
Published: (2021)

An evaluation framework for synthetic data generation models
by: Livieris, Ioannis E., et al.
Published: (2024)

Location Leakage in Federated Signal Maps
by: Bakopoulou, Evita, et al.
Published: (2021)

The Effects of Data Imbalance Under a Federated Learning Approach for Credit Risk Forecasting
by: Zhang, Shuyao, et al.
Published: (2024)

Exploiting temporal parallelism for LSTM Autoencoder acceleration on FPGA
by: Leftheriotis, Aimilios, et al.
Published: (2026)

TF2AIF: Facilitating development and deployment of accelerated AI models on the cloud-edge continuum
by: Leftheriotis, Aimilios, et al.
Published: (2024)

Deep TPC: Temporal-Prior Conditioning for Time Series Forecasting
by: Bellos, Filippos, et al.
Published: (2026)

Trend Extrapolation for Technology Forecasting: Leveraging LSTM Neural Networks for Trend Analysis of Space Exploration Vessels
by: Tsai, Peng-Hung, et al.
Published: (2025)

CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
by: Bhatia, Randeep, et al.
Published: (2025)

Metanetworks as Regulatory Operators: Learning to Edit for Requirement Compliance
by: Kalogeropoulos, Ioannis, et al.
Published: (2025)

REFOL: Resource-Efficient Federated Online Learning for Traffic Flow Forecasting
by: Liu, Qingxiang, et al.
Published: (2024)

HSTFL: A Heterogeneous Federated Learning Framework for Misaligned Spatiotemporal Forecasting
by: Cai, Shuowei, et al.
Published: (2024)

Colliding with Adversaries at ECML-PKDD 2025 Adversarial Attack Competition 1st Prize Solution
by: Stefanopoulos, Dimitris, et al.
Published: (2025)

Exploring Lightweight Federated Learning for Distributed Load Forecasting
by: Duttagupta, Abhishek, et al.
Published: (2024)