Machine Learning and Principles and Practice of Knowledge Discovery in Databases

.- Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial.

.- Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces.

.- Predicate-based explanation of a Reinforcement Learning agent via action importance evaluation.

.- Local interpretability of random forests for multi-target regression.

.- On the Adaptability of Attention-Based Interpretability in Different Transformer Architectures for Multi-Class Classification Tasks.

.- Analyzing the Explanation and Interpretation Potential of Matrix Capsule Networks.

.- An Efficient Shapley Value Computation for the Naive Bayes Classifier.

.- An Experimental Investigation into the Evaluation of Explainability Methods for Computer Vision.

.- Natively Interpretable t-SNE.

.- BIAS 2023 - 3rd Workshop on Bias and Fairness in AI.

.- Automated discovery of trade-off between utility, privacy and fairness in machine learning models.

.- Facial Analysis Systems and Down Syndrome.

.- Mitigating Discrimination in Insurance with Wasserstein Barycenters.

.- Counterfactual Explanations for Recommendation Bias.

.- Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias.

.- Towards Fair Face Verification: An In-depth Analysis of Demographic Biases.

.- How Different Is Stereotypical Bias Across Languages?.

.- Sampling strategies for mitigating bias in face synthesis methods.

.- Towards Inclusive Fairness Evaluation via Eliciting Disagreement Feedback from Non-Expert Stakeholders.

.- Beliefs, Relationships, and Equality: An Alternative Source of Discrimination in a Symmetric Hiring Market via Threats.

.- Biased Data in Conversational Agents.

.- Stars, Stripes, and Silicon: Unravelling the ChatGPT's All-American, Monochrome, Cis-centric Bias.

.- How Prevalent is Gender Bias in ChatGPT? - Exploring German and English ChatGPT Responses.

.- Explainable Artificial Intelligence: From Static to Dynamic.

.- Shapley-Based Feature Selection for Online Algorithm Selection.

.- Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes.

.- Dynamic Interpretability for Model Comparison via Decision Rules.

.- Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learning.

.- A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning.

.- ML, Law and Society.

.- The AI Act Is Coming: Are E-Health Manufacturers Ready?.

.- Techniques to achieve anonymisation of health data: When are they sufficient to be considered as legally complaint?.

.- Mental state classification using EEG signals: ethics, law and challenges.

.- Trustworthy AI Development in Education.

.- Variants analysis in judicial trials: Challenges and initial results.

.- FLAIRS: Federated Learning AI Regulatory Sandbox.

.- Towards a Process View of Algorithmic Fairness.

.- A practical application of Artificial Intelligence techniques for legal context analysis.

.- Why Fair Automated Hiring Systems Breach EU Non-Discrimination Law.

.- Enhancing e-Justice: Assessing the effectiveness of specialized LLMs' applications with Cicero.

.- Process mining on a public procurement dataset: a case study.

.- Google Topics as a way out of the cookie dilemma?.