Results 131 to 140 of about 7,049,980 (289)

DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

Journal of Forecasting, EarlyView.
ABSTRACT This paper compares within‐sample and out‐of‐sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets, and Wouters model is the chosen laboratory using quarterly real‐time euro area data vintages, covering 2001Q1–2019Q4.
Anders Warne
wiley   +1 more source

Enhancing federated learning for IoT-based anomaly detection: A reputation-based client selection approach

Alexandria Engineering Journal
Federated Learning (FL) enables collaborative model training across decentralized, privacy-sensitive environments but often suffers from slow convergence, unbalanced client selection, and non‑IID data challenges.
Maha Jawad Alfadhil, Ali Baydoun, Moutaz Alazab, Hafeez Ur Rehman, Jihad Al Jaam, Sumaya Ali S.A. Al-Maadeed   +5 more
doaj   +1 more source

Analyzing the Impact of Non-IID Data on IoT-Enabled Federated Learning for ECG Arrhythmia Detection

The integration of Federated Learning (FL) in the Internet of Medical Things (IoMT) represents a cutting-edge solution, enabling the training of Artificial Intelligence (AI) models directly on edge devices without the need to share sensitive patient ...
Massimo De Vittorio, Gianluigi Semeraro, Davide Cantoro, Angela-Tafadzwa Shumba, Teodoro Montanaro, Ilaria Sergi, Luigi Patrono   +6 more
core   +1 more source

Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now

Journal of Forecasting, EarlyView.
ABSTRACT We propose PRISM‐Now, a novel ensemble forecasting system for near‐term GDP projection. Recognizing that relevant economic information evolves over time, we treat forecasts from multiple base models as draws from a mixture distribution of “good” and “bad” estimates, whose composition changes continuously and cannot be identified ex ante.
Beomseok Seo, Hyungbae Cho, Dongjae Lee
wiley   +1 more source

Entropy-Regularized Federated Optimization for Non-IID Data

Algorithms
Federated learning (FL) struggles under non-IID client data when local models drift toward conflicting optima, impairing global convergence and performance. We introduce entropy-regularized federated optimization (ERFO), a lightweight client-side modification that augments each local objective with a Shannon entropy penalty on the per-parameter update ...
openaire   +1 more source

Nowcasting World Trade With Machine Learning: A Three‐Step Approach

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn, Baptiste Meunier, Sebastian Stumpner   +2 more
wiley   +1 more source

FedDB: A Federated Learning Approach Using DBSCAN for DDoS Attack Detection

Applied Sciences
The rise of Distributed Denial of Service (DDoS) attacks on the internet has necessitated the development of robust and efficient detection mechanisms. DDoS attacks continue to present a significant threat, making it imperative to find efficient ways to ...
Yi-Chen Lee, Wei-Che Chien, Yao-Chung Chang   +2 more
doaj   +1 more source

Threshold Asymmetric Conditional Autoregressive Range (TACARR) Model

Journal of Forecasting, EarlyView.
ABSTRACT This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed ...
Isuru Ratnayake, V. A. Samaranayake
wiley   +1 more source

Comparative Analysis of Centralized and Federated Intrusion Detection in IoT-Enabled Cyber-Physical Systems Under Data and Label-Skew

IEEE Access
Cyber-Physical Systems (CPS) increasingly leverage Internet of Things (IoT) technologies to enable seamless communication and control across distributed devices.
Muhammad Ali Khan, Rao Naveed Bin Rais, Osman Khalid, Mohamed Deriche   +3 more
doaj   +1 more source

Climate Change Laws and European Stock Markets: An Event Analysis

International Journal of Finance &Economics, EarlyView.
ABSTRACT Under the context of the climate change we assess the impact of EU's legislative initiative on European stock markets. Specifically, we focus on its impact on energy and Environmental Social Governance (ESG) sectors for equity returns and volatility for a representative basket of EU countries (participating also in Eurozone) as well as ...
Theodoros Bratis, Georgios P. Kouretas, Evangelos Salachas   +2 more
wiley   +1 more source