Sökning: "Syntetisk Datagenerering"
Visar resultat 1 - 5 av 9 uppsatser innehållade orden Syntetisk Datagenerering.
1. Evaluating Membership Inference Attacks on Synthetic Data Generated With Formal Privacy Guarantees
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Synthetic data generation using generative machine learning has been increasinglypublicized as a new tool for data anonymization. It promises to offer privacy whilemaintaining the statistical properties of the original dataset. This study focuses on the riskswith synthetic data by looking mainly at two aspects: privacy and utility. LÄS MER
2. Synthetic data generation for domain adaptation of a retriever-reader Question Answering system for the Telecom domain : Comparing dense embeddings with BM25 for Open Domain Question Answering
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Having computer systems capable of answering questions has been a goal within Natural Language Processing research for many years. Machine Learning systems have recently become increasingly proficient at this task with large language models obtaining state-of-the-art performance. LÄS MER
3. Energy-Efficient Private Forecasting on Health Data using SNNs
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Health monitoring devices, such as Fitbit, are gaining popularity both as wellness tools and as a source of information for healthcare decisions. Predicting such wellness goals accurately is critical for the users to make informed lifestyle choices. LÄS MER
4. Multivariate Time Series Data Generation using Generative Adversarial Networks : Generating Realistic Sensor Time Series Data of Vehicles with an Abnormal Behaviour using TimeGAN
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Large datasets are a crucial requirement to achieve high performance, accuracy, and generalisation for any machine learning task, such as prediction or anomaly detection, However, it is not uncommon for datasets to be small or imbalanced since gathering data can be difficult, time-consuming, and expensive. In the task of collecting vehicle sensor time series data, in particular when the vehicle has an abnormal behaviour, these struggles are present and may hinder the automotive industry in its development. LÄS MER
5. Privacy-preserving Synthetic Data Generation for Healthcare Planning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Recently, a variety of machine learning techniques have been applied to different healthcare sectors, and the results appear to be promising. One such sector is healthcare planning, in which patient data is used to produce statistical models for predicting the load on different units of the healthcare system. LÄS MER