167 citations · 210 across the 72 of their papers we have counts for
7 papers · 1 filter
Optimal Recourse Summaries via Bi-Objective Decision Tree Learning
Ioannis Chatzis, Jason Liartis, Athanasios Voulodimos +1
Actionable Recourse provides individuals with actions they can take to change an unfavorable classifier outcome. While useful at the instance level, it is ill-suited for global aud…
Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen +3
Learning to cooperate in distributed partially observable environments with no communication abilities poses significant challenges for multi-agent deep reinforcement learning (MAR…
Semantic-Aware Interpretable Multimodal Music Auto-Tagging
Andreas Patakis, Vassilis Lyberatos, Spyridon Kantarelis +2
Music auto-tagging is essential for organizing and discovering music in extensive digital libraries. While foundation models achieve exceptional performance in this domain, their o…
Semantic Prototypes: Enhancing Transparency Without Black Boxes
Orfeas Menis-Mastromichalakis, Giorgos Filandrianos, Jason Liartis +2
As machine learning (ML) models and datasets increase in complexity, the demand for methods that enhance explainability and interpretability becomes paramount. Prototypes, by encap…
Beyond One-Size-Fits-All: Adapting Counterfactual Explanations to User Objectives
Orfeas Menis Mastromichalakis, Jason Liartis, Giorgos Stamou
Explainable Artificial Intelligence (XAI) has emerged as a critical area of research aimed at enhancing the transparency and interpretability of AI systems. Counterfactual Explanat…
Graph Edits for Counterfactual Explanations: A comparative study
Angeliki Dimitriou, Nikolaos Chaidos, Maria Lymperaiou +1
Counterfactuals have been established as a popular explainability technique which leverages a set of minimal edits to alter the prediction of a classifier. When considering concept…
A survey on knowledge-enhanced multimodal learning
Maria Lymperaiou, Giorgos Stamou
Multimodal learning has been a field of increasing interest, aiming to combine various modalities in a single joint representation. Especially in the area of visiolinguistic (VL) l…