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Distributed ledger technology for decentralized identity management – Complete Phd and Masters Thesis

[ad_1] Introduction: In recent years, there has been a growing interest in the potential of Distributed Ledger Technology (DLT) to revolutionize various industries, including identity management. Decentralized identity management using DLT has the potential to…

Homomorphic encryption for privacy-preserving deep learning – Complete Phd and Masters Thesis

[ad_1] Introduction With the increasing use of deep learning in various industries, there is a growing concern about the privacy of sensitive data that is used to train these models. Homomorphic encryption has emerged as…

Serverless computing for big data analytics – Complete Phd and Masters Thesis

[ad_1] Introduction: Serverless computing has emerged as a promising technology for big data analytics, offering a scalable and cost-effective solution for processing and analyzing large volumes of data. With serverless computing, developers can focus on…

Generative adversarial networks for text-to-image synthesis – Complete Phd and Masters Thesis

[ad_1] Introduction: Generative adversarial networks (GANs) have gained significant attention in recent years for their ability to generate realistic images from text descriptions. In the field of text-to-image synthesis, GANs have shown promising results in…

Secure multi-party computation for secure linear regression – Complete Phd and Masters Thesis

[ad_1] Introduction Secure multi-party computation (MPC) is a cryptographic technique that allows multiple parties to jointly compute a function over their private inputs without revealing any information other than the output. This technology has gained…

Reinforcement learning for robotic manipulation – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, robotic manipulation has gained significant attention due to its potential applications in various industries such as manufacturing, healthcare, and agriculture. Reinforcement learning, a type of machine learning algorithm, has shown…

Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) for verifiable federated learning – Complete Phd and Masters Thesis

[ad_1] Introduction Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a powerful cryptographic tool for ensuring privacy and security in various applications. In the context of federated learning, where multiple parties collaborate to…

Federated transfer learning for cross-device federated learning – Complete Phd and Masters Thesis

[ad_1] Introduction In the era of big data and connected devices, federated learning has emerged as a promising approach to collaborative machine learning without compromising data privacy. Federated transfer learning extends the concept of federated…

Quantum machine learning for quantum error correction – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum computing is a rapidly evolving field that has the potential to revolutionize the way we process and analyze data. Quantum machine learning is an emerging area of research that combines principles of…

Zero-shot learning for cross-modal retrieval – Complete Phd and Masters Thesis

[ad_1] Introduction Chapter 1: Introduction 1.1 Introduction 1.2 Background of study 1.3 Problem Statement 1.4 Objective of study 1.5 Limitation of study 1.6 Scope of study 1.7 Significance of study 1.8 Structure of the Thesis…

Tag: information technology master’s program