Interpretable and Fair Mechanisms for Abstaining Classifiers
Fuente:
arXiv
Saved in:
| Main Authors: | Lenders, Daphne, Pugnana, Andrea, Pellungrini, Roberto, Calders, Toon, Pedreschi, Dino, Giannotti, Fosca |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Interpretable and Fair Mechanisms for Abstaining Classifiers
by: Lenders, Daphne, et al.
Published: (2024)
by: Lenders, Daphne, et al.
Published: (2024)
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems
by: Punzi, Clara, et al.
Published: (2024)
by: Punzi, Clara, et al.
Published: (2024)
Mathematical Foundation of Interpretable Equivariant Surrogate Models
by: Colombini, Jacopo Joy, et al.
Published: (2025)
by: Colombini, Jacopo Joy, et al.
Published: (2025)
Explanations Go Linear: Post-hoc Explainability for Tabular Data with Interpretable Meta-Encoding
by: Piaggesi, Simone, et al.
Published: (2025)
by: Piaggesi, Simone, et al.
Published: (2025)
Comparing Explanations is Not Enough, Explain the Change: New Standards are Needed to Explain Behavioral Shifts in Large Language Models
by: Ciaperoni, Martino, et al.
Published: (2026)
by: Ciaperoni, Martino, et al.
Published: (2026)
Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
by: Pugnana, Andrea, et al.
Published: (2025)
by: Pugnana, Andrea, et al.
Published: (2025)
How to be fair? A study of label and selection bias
by: Favier, Marco, et al.
Published: (2024)
by: Favier, Marco, et al.
Published: (2024)
Learning by Surprise: Surplexity for Mitigating Model Collapse in Generative AI
by: Gambetta, Daniele, et al.
Published: (2024)
by: Gambetta, Daniele, et al.
Published: (2024)
The Diversity Paradox revisited: Systemic Effects of Feedback Loops in Recommender Systems
by: Barlacchi, Gabriele, et al.
Published: (2026)
by: Barlacchi, Gabriele, et al.
Published: (2026)
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges
by: Prado-Romero, Mario Alfonso, et al.
Published: (2022)
by: Prado-Romero, Mario Alfonso, et al.
Published: (2022)
"Patriarchy Hurts Men Too." Does Your Model Agree? A Discussion on Fairness Assumptions
by: Favier, Marco, et al.
Published: (2024)
by: Favier, Marco, et al.
Published: (2024)
Cherry on the Cake: Fairness is NOT an Optimization Problem
by: Favier, Marco, et al.
Published: (2024)
by: Favier, Marco, et al.
Published: (2024)
One-Shot Clustering for Federated Learning
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
One-Shot Clustering for Federated Learning Under Clustering-Agnostic Assumption
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
Deep Neural Network Benchmarks for Selective Classification
by: Pugnana, Andrea, et al.
Published: (2024)
by: Pugnana, Andrea, et al.
Published: (2024)
Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Models
by: Bortolotti, Samuele, et al.
Published: (2026)
by: Bortolotti, Samuele, et al.
Published: (2026)
A Causal Framework for Evaluating Deferring Systems
by: Palomba, Filippo, et al.
Published: (2024)
by: Palomba, Filippo, et al.
Published: (2024)
Multiclass Local Calibration with the Jensen-Shannon Distance
by: Barbera, Cesare, et al.
Published: (2025)
by: Barbera, Cesare, et al.
Published: (2025)
Divide et Calibra: Multiclass Local Calibration via Vector Quantization
by: Barbera, Cesare, et al.
Published: (2026)
by: Barbera, Cesare, et al.
Published: (2026)
Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
by: Heng, Alvin, et al.
Published: (2025)
by: Heng, Alvin, et al.
Published: (2025)
Bounded-Abstention Pairwise Learning to Rank
by: Ferrara, Antonio, et al.
Published: (2025)
by: Ferrara, Antonio, et al.
Published: (2025)
Simple and Effective Specialized Representations for Fair Classifiers
by: Sinigaglia, Alberto, et al.
Published: (2025)
by: Sinigaglia, Alberto, et al.
Published: (2025)
Fairness of Classifiers in the Presence of Constraints between Features
by: Cooper, Martin C., et al.
Published: (2026)
by: Cooper, Martin C., et al.
Published: (2026)
Demystifying the Optimal Fair Classifier in Multi-Class Classification
by: Zhang, Li, et al.
Published: (2026)
by: Zhang, Li, et al.
Published: (2026)
Clarify, Abstain or Answer? Strategising in Conversation with Belief-Augmented Generation
by: Baan, Joris, et al.
Published: (2026)
by: Baan, Joris, et al.
Published: (2026)
Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery
by: Cinquini, Martina, et al.
Published: (2023)
by: Cinquini, Martina, et al.
Published: (2023)
To Ask or Not to Ask: Learning to Require Human Feedback
by: Pugnana, Andrea, et al.
Published: (2025)
by: Pugnana, Andrea, et al.
Published: (2025)
Reranking individuals: The effect of fair classification within-groups
by: Goethals, Sofie, et al.
Published: (2024)
by: Goethals, Sofie, et al.
Published: (2024)
No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models
by: Legast, Magali, et al.
Published: (2026)
by: Legast, Magali, et al.
Published: (2026)
Closed-Form Interpretation of Neural Network Classifiers with Symbolic Gradients
by: Wetzel, Sebastian Johann
Published: (2024)
by: Wetzel, Sebastian Johann
Published: (2024)
Standardized Interpretable Fairness Measures for Continuous Risk Scores
by: Becker, Ann-Kristin, et al.
Published: (2023)
by: Becker, Ann-Kristin, et al.
Published: (2023)
FADE: Towards Fairness-aware Generation for Domain Generalization via Classifier-Guided Score-based Diffusion Models
by: Lin, Yujie, et al.
Published: (2024)
by: Lin, Yujie, et al.
Published: (2024)
Debiasing Text Safety Classifiers through a Fairness-Aware Ensemble
by: Sturman, Olivia, et al.
Published: (2024)
by: Sturman, Olivia, et al.
Published: (2024)
When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers via Membership Inference Attacks
by: Tian, Huan, et al.
Published: (2023)
by: Tian, Huan, et al.
Published: (2023)
XNB: Explainable Class-Specific NaIve-Bayes Classifier
by: Aguilar-Ruiz, Jesus S., et al.
Published: (2024)
by: Aguilar-Ruiz, Jesus S., et al.
Published: (2024)
Hybrid Retrieval for Hallucination Mitigation in Large Language Models: A Comparative Analysis
by: Mala, Chandana Sree, et al.
Published: (2025)
by: Mala, Chandana Sree, et al.
Published: (2025)
Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices
by: Reusens, Manon, et al.
Published: (2026)
by: Reusens, Manon, et al.
Published: (2026)
Hyperparameter Importance Analysis for Multi-Objective AutoML
by: Theodorakopoulos, Daphne, et al.
Published: (2024)
by: Theodorakopoulos, Daphne, et al.
Published: (2024)
Perspectives in Play: A Multi-Perspective Approach for More Inclusive NLP Systems
by: Muscato, Benedetta, et al.
Published: (2025)
by: Muscato, Benedetta, et al.
Published: (2025)
Semi Supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-Labelling
by: Dantas, Cassio F., et al.
Published: (2024)
by: Dantas, Cassio F., et al.
Published: (2024)
Similar Items
-
Interpretable and Fair Mechanisms for Abstaining Classifiers
by: Lenders, Daphne, et al.
Published: (2024) -
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems
by: Punzi, Clara, et al.
Published: (2024) -
Mathematical Foundation of Interpretable Equivariant Surrogate Models
by: Colombini, Jacopo Joy, et al.
Published: (2025) -
Explanations Go Linear: Post-hoc Explainability for Tabular Data with Interpretable Meta-Encoding
by: Piaggesi, Simone, et al.
Published: (2025) -
Comparing Explanations is Not Enough, Explain the Change: New Standards are Needed to Explain Behavioral Shifts in Large Language Models
by: Ciaperoni, Martino, et al.
Published: (2026)