Essays about: "randomization"
Showing result 6 - 10 of 42 essays containing the word randomization.
-
6. Data mining in healthcare : A security and privacy perspective
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Data mining has become an essential tool in various domains, including healthcare, for finding patterns and relationships in large datasets to solve business issues. However, given the sensitivity of healthcare data, safeguarding confidentiality and privacy to protect patient information is highly prioritized. READ MORE
-
7. Extremal Mechanisms for Pointwise Maximal Leakage
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to implement privacy preservation for individuals, systems need to utilize privacy mechanisms that privatize sensitive data by randomization. The goal of privacy mechanism design is to find optimal tradeoffs between maximizing the utility of the privatized data while providing a strict sense of privacy defined by a chosen privacy measure. READ MORE
-
8. Targeted Improvement of a Deep Learning Object Detector Using Synthetic Training Data
University essay from Lunds universitet/Matematisk statistikAbstract : When working with object detection, the quality and quantity of the training data is often a recurrent bottleneck. This thesis proposes a technique of incrementally improving an object detector using synthetically rendered data. READ MORE
-
9. Domain Adaptation to Meet the Reality-Gap from Simulation to Reality
University essay from Linköpings universitet/DatorseendeAbstract : Being able to train machine learning models on simulated data can be of great interest in several applications, one of them being for autonomous driving of cars. The reason is that it is easier to collect large labeled datasets as well as performing reinforcement learning in simulations. READ MORE
-
10. Confounder Parsing for Text Matching
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : In observational studies for policy evaluation, matching is used in service of causal inference to simulate randomization and thus reduce selection bias that might occur when treatment assignment differs systematically. This is done by balancing the distribution of confounding covariates measured before treatments. READ MORE
