6 papers
Source-Free Cross-Domain Continual Learning
Muhammad Tanzil Furqon, Mahardhika Pratama, Igor Škrjanc +3
Although existing cross-domain continual learning approaches successfully address many streaming tasks having domain shifts, they call for a fully labeled source domain hindering t…
A Neuro-Fuzzy System for Interpretable Long-Term Stock Market Forecasting
Miha Ožbot, Igor Škrjanc, Vitomir Štruc
In the complex landscape of multivariate time series forecasting, achieving both accuracy and interpretability remains a significant challenge. This paper introduces the Fuzzy Tran…
Black-Box Time-Series Domain Adaptation via Cross-Prompt Foundation Models
M. T. Furqon, Mahardhika Pratama, Igor Skrjanc +3
The black-box domain adaptation (BBDA) topic is developed to address the privacy and security issues where only an application programming interface (API) of the source model is av…
Measures of Overlapping Multivariate Gaussian Clusters in Unsupervised Online Learning
Miha Ožbot, Igor Škrjanc
In this paper, we propose a new measure for detecting overlap in multivariate Gaussian clusters. The aim of online learning from data streams is to create clustering, classificatio…
Federated Learning based on Self-Evolving Gaussian Clustering
Miha Ožbot, Igor Škrjanc
In this study, we present an Evolving Fuzzy System within the context of Federated Learning, which adapts dynamically with the addition of new clusters and therefore does not requi…
From Model-Based and Adaptive Control to Evolving Fuzzy Control
Daniel Leite, Igor Škrjanc, Fernando Gomide
Evolving fuzzy systems build and adapt fuzzy models - such as predictors and controllers - by incrementally updating their rule-base structure from data streams. On the occasion of…