most citedCrisp complexity of fuzzy classifiers

1 citations · 1 across the 8 of their papers we have counts for

collaborators

11 papers

cs.LO2026

Reconstruction of continuous Archimedean t-norms from their section along an increasing curve

Gabriel Bauza-Llompart, Raquel Fernandez-Peralta, Marc Munar

The completion problem for continuous and Archimedean triangular norms (t-norms for short) consists in describing all the operators that take predefined values on a given subset of…

math.GM2026

A lattice-theoretic framework for hesitant fuzzy convexity beyond scalar observables

Carlos Salvatierra, Pedro Huidobro, Raquel Fernandez-Peralta

In fuzzy-set theory, the notion of convexity has often been formulated through scalar reductions, typically via scores and aggregation functions. Although useful, such reductions m…

cs.LG2026

Hypernetworks for Dynamic Feature Selection

Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez

Dynamic feature selection (DFS) is a machine learning framework in which features are acquired sequentially for individual samples under budget constraints. The exponential growth…

cs.LG2025

A Fast Interpretable Fuzzy Tree Learner

Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez

Fuzzy rule-based systems have been mostly used in interpretable decision-making because of their interpretable linguistic rules. However, interpretability requires both sensible li…

cs.AI2025

On the Non-Uniqueness of Representation of -Implications

Raquel Fernandez-Peralta, Andrea Mesiarová-Zemánková

Fuzzy implication functions constitute fundamental operators in fuzzy logic systems, extending classical conditionals to manage uncertainty in logical inference. Among the extensiv…

cs.AI2025

A global view of diverse construction methods of fuzzy implication functions rooted on F-chains

Raquel Fernandez-Peralta, Juan Vicente Riera

Fuzzy implication functions are one of the most important operators used in the fuzzy logic framework. While their flexible definition allows for diverse families with distinct pro…

cs.LG2025

Model-Agnostic Dynamic Feature Selection with Uncertainty Quantification

Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez

Dynamic feature selection (DFS) addresses budget constraints in decision-making by sequentially acquiring features for each instance, making it appealing for resource-limited scena…

cs.AI2025★ 1 cited

Crisp complexity of fuzzy classifiers

Raquel Fernandez-Peralta, Javier Fumanal-Idocin, Javier Andreu-Perez

Rule-based systems are a very popular form of explainable AI, particularly in the fuzzy community, where fuzzy rules are widely used for control and classification problems. Howeve…

cs.LO2025

Fuzzy Implicative Rules: A Unified Approach

Raquel Fernandez-Peralta

Rule mining algorithms are one of the fundamental techniques in data mining for disclosing significant patterns in terms of linguistic rules expressed in natural language. In this…

cs.AI2025

A Comprehensive Survey of Fuzzy Implication Functions

Raquel Fernandez-Peralta

Fuzzy implication functions are a key area of study in fuzzy logic, extending the classical logical conditional to handle truth degrees in the interval . While existing lite…

cs.LG2025

Compact Rule-Based Classifier Learning via Gradient Descent

Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez

Rule-based models are essential for high-stakes decision-making due to their transparency and interpretability, but their discrete nature creates challenges for optimization and sc…