Results 111 to 120 of about 109,032 (273)
Advanced Optimization Techniques for Federated Learning on Non-IID Data
Future InternetFederated learning enables model training on multiple clients locally, without the need to transfer their data to a central server, thus ensuring data privacy.
Filippos Efthymiadis +3 more
doaj +1 more source
Bayesian clustering of multivariate extremes
Canadian Journal of Statistics, EarlyView.Abstract The asymptotic dependence structure between multivariate extreme values is fully characterized by their projections on the unit simplex. Under mild conditions, the only constraint on the resulting distributions is that their marginal means must be equal, which results in a nonparametric model that can be difficult to use in applications ...
Sonia Alouini, Anthony C. Davison
wiley +1 more source
FedDB: A Federated Learning Approach Using DBSCAN for DDoS Attack Detection
Applied SciencesThe 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 +2 more
doaj +1 more source
Waves of Uncertainty: Crude Oil Under Geopolitical, Economic, and ESG Turbulence
Energy Science &Engineering, EarlyView.Dynamic copula and wavelet coherence reveal that geopolitical, economic, and sustainability uncertainties significantly shape crude oil price co‐movements. Long‐term coherence, especially post‐2015, highlights the growing role of ESG risks alongside geopolitical shocks and economic crises in global energy risk transmission.
Sana Braiek +3 more
wiley +1 more source
PFL-NON-IID Framework: Evaluating MOON Algorithm on Handling Non-IID Data Distributions
, 2023 Sheng Chen +3 more
openaire +1 more source
Mortality Forecasting Using Variational Inference
Journal of Forecasting, EarlyView.ABSTRACT This paper considers the problem of forecasting mortality rates. A large number of models have already been proposed for this task, but they generally have the disadvantage of either estimating the model in a two‐step process, possibly losing efficiency, or relying on methods that are cumbersome for the practitioner to use.
Patrik Andersson, Mathias Lindholm
wiley +1 more source
A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets
Journal of Forecasting, EarlyView.ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley +1 more source
IEEE AccessCyber-Physical Systems (CPS) increasingly leverage Internet of Things (IoT) technologies to enable seamless communication and control across distributed devices.
Muhammad Ali Khan +3 more
doaj +1 more source
Journal of Forecasting, EarlyView.ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source
Few-Shot Class-Incremental Learning With Non-IID Decentralized Data
IEEE Internet of Things JournalFew-shot class-incremental learning is crucial for developing scalable and adaptive intelligent systems, as it enables models to acquire new classes with minimal annotated data while safeguarding the previously accumulated knowledge. Nonetheless, existing methods deal with continuous data streams in a centralized manner, limiting their applicability in
Cuiwei Liu +5 more
openaire +2 more sources