Machine Learning and Principles and Practice of Knowledge Discovery in Databases
portes grátis
Machine Learning and Principles and Practice of Knowledge Discovery in Databases
International Workshops of ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers, Part I
Meo, Rosa; Silvestri, Fabrizio
Springer International Publishing AG
11/2024
575
Mole
9783031746291
Pré-lançamento - envio 15 a 20 dias após a sua edição
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.- 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?.
.- 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?.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
artificial intelligence;computer security;data security;distributed systems;software design;software engineering;neural networks;bayesian networks;computer vision;information retrieval;semantics;fuzzy sets;inference engines;image processing
.- 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?.
.- 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?.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
