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Bayesian Network-Based Multi-objective Estimation of Distribution Algorithm for Feature Selection Tailored to Regression Problems
Feature selection is an essential pre-processing step in Machine Learning for improving the performance of models, reducing the time of predictions,...
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Applying Genetic Algorithms to Validate a Conjecture in Graph Theory: The Minimum Dominating Set Problem
This paper presents a case study where the interdisciplinary approach between artificial intelligence, specifically genetic algorithms, and discrete...
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Multiresolution Controller Based on Window Function Networks for a Quanser Helicopter
To improve neural network (NN) performance, new activation functions, such as ReLU, GELU, and SELU, to name a few, have been proposed. Windows-based...
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Load Demand Forecasting Using a Long-Short Term Memory Neural Network
Electric power load forecasting is very important for the operation and the planning of a utility company. Decisions of the electric market, electric...
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Nonlinear DIP-DiracVTV Model for Color Image Restoration
Variational models for inverse problems are mainly based on the choice of the regularizer, whose goal is to give the solutions some desirable...
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Reasoning in DL- \(Lite_R\) Based Knowledge Base Under Category Semantics
We propose in this paper a rewriting of the usual set-theoretical semantics of the Description Logic DL-...
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Secure and Privacy-Preserving Authentication for Data Subject Rights Enforcement
In light of the GDPR, data controllers (DC) need to allow data subjects (DS) to exercise certain data subject rights. A key requirement here is that...
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Assuring GDPR Conformance Through Language-Based Compliance
Existing legal regulations, such as the GDPR in the European Union, exert significant pressure on businesses to embed legal principles into their...
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The Effacement of Information Technology from EU Law: The Need for Collaborative Approaches to Redesign the EU’s Regulatory Architecture
EU information technology law is built like a multi-storey house: on the ground floor is technology development and on the top floor are regulatory...
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Privacy and Utility Evaluation of Synthetic Tabular Data for Machine Learning
Synthetic data generation approaches have attracted a lot of attention as a potential substitute for classical anonymization methods. However,...
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Enhancing Transparency Through Personal Information Management Systems: Current State of Service Offerings and Considerations for Further Advancements
The aim of the present article is to analyze how Personal Information Management Systems may alleviate current problems in assuring the principle of...
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Empirical Evaluation of Synthetic Data Created by Generative Models via Attribute Inference Attack
The disclosure risk of synthetic/artificial data is still being determined. Studies show that synthetic data generation techniques generate similar...
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Towards Privacy-Preserving Machine Learning in Sovereign Data Spaces: Opportunities and Challenges
The world of big data has unlocked novel avenues for organizations to generate value via sharing data. Current data ecosystem initiatives such as...
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A Unified Approach to Learning with Label Noise and Unsupervised Confidence Approximation
Noisy label training is the problem of training a neural network from a dataset with errors in the labels. Selective prediction is the problem of...
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Transesophageal Echocardiography Generation Using Anatomical Models
Through automation, deep learning (DL) can enhance the analysis of transesophageal echocardiography (TEE) images. However, DL methods require large...
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URL: Combating Label Noise for Lung Nodule Malignancy Grading
Due to the complexity of annotation and inter-annotator variability, most lung nodule malignancy grading datasets contain label noise, which...
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Proportion Estimation by Masked Learning from Label Proportion
The PD-L1 rate, the number of PD-L1 positive tumor cells over the total number of all tumor cells, is an important metric for immunotherapy. This...
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Modular, Label-Efficient Dataset Generation for Instrument Detection for Robotic Scrub Nurses
Surgical instrument detection is a fundamental task of a robotic scrub nurse. For this, image-based deep learning techniques are effective but...
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LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation
Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used...