Search for dissertations about: "privacy-preserving machine learning"
Showing result 1 - 5 of 15 swedish dissertations containing the words privacy-preserving machine learning.
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1. Towards Privacy Preserving Micro-data Analysis : A machine learning based perspective under prevailing privacy regulations
Abstract : Machine learning (ML) has been employed in a wide variety of domains where micro-data (i.e., personal data) are used in the training process. READ MORE
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2. Towards Privacy Preserving Intelligent Systems
Abstract : Intelligent systems, i.e., digital systems containing smart devices that can gather, analyze, and act in response to the data they collect from their surrounding environment, have progressed from theory to application especially in the last decade, thanks to the recent technological advances in sensors and machine learning. READ MORE
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3. Privacy preserving behaviour learning for the IoT ecosystem
Abstract : IoT has enabled the creation of a multitude of personal applications and services for a better understanding and improvement of urban environments and our personal lives. These services are driven by the continuous collection and analysis of sensitive and private user data to provide personalised experiences. READ MORE
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4. Parameter Estimation : Towards Data-Driven and Privacy Preserving Approaches
Abstract : Parameter estimation is a pivotal task across various domains such as system identification, statistics, and machine learning. The literature presents numerous estimation procedures, many of which are backed by well-studied asymptotic properties. READ MORE
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5. Towards Scalable Machine Learning with Privacy Protection
Abstract : The increasing size and complexity of datasets have accelerated the development of machine learning models and exposed the need for more scalable solutions. This thesis explores challenges associated with large-scale machine learning under data privacy constraints. READ MORE