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Zero-shot learning for relation extraction – Complete Phd and Masters Thesis

[ad_1] Introduction: Zero-shot learning for relation extraction is an emerging field in natural language processing that aims to extract relations between entities without requiring any labeled training data for those specific relations. Traditional relation extraction…

Transfer learning for cross-modal sentiment analysis – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, sentiment analysis has gained significant attention in various application domains such as social media, e-commerce, and customer feedback analysis. Sentiment analysis aims to identify and extract subjective information from textual…

Quantum key distribution for secure quantum communication – Complete Phd and Masters Thesis

[ad_1] Introduction: Quantum key distribution (QKD) is a method of secure communication that utilizes the principles of quantum mechanics to generate and distribute cryptographic keys. With the rise of quantum computing and the potential threat…

Zero-knowledge proofs for privacy-preserving smart metering – Complete Phd and Masters Thesis

[ad_1] Introduction Zero-knowledge proofs have gained significant attention in recent years for their potential to enhance privacy in various applications, including smart metering systems. Smart meters are essential components of modern energy grids, providing real-time…

Generative adversarial networks for video prediction – Complete Phd and Masters Thesis

[ad_1] Thesis Overview: Title: Generative Adversarial Networks for Video Prediction Introduction: Generative adversarial networks (GANs) have gained significant attention in recent years for their ability to generate realistic data samples. Video prediction is a challenging…

Secure multi-party computation for privacy-preserving federated learning – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, federated learning has gained significant attention as a privacy-preserving technique for training machine learning models on distributed data sources. However, one of the key challenges in federated learning is ensuring…

Explainable deep learning for time series forecasting – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, deep learning has become a popular and powerful approach for solving complex machine learning problems, including time series forecasting. However, one of the main challenges with deep learning models is…

Quantum-resistant secure multi-party computation – Complete Phd and Masters Thesis

[ad_1] Introduction: Quantum computing has the potential to revolutionize the field of cryptography by breaking many of the commonly used encryption schemes. As quantum computers become more powerful, it is crucial to develop secure multi-party…

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

[ad_1] Introduction Federated transfer learning is a cutting-edge technique that allows for the sharing of knowledge across multiple devices while preserving data privacy and security. This emerging field has gained significant attention in recent years…

Decentralized digital rights management using blockchain – Complete Phd and Masters Thesis

[ad_1] Introduction As the digital world continues to expand rapidly, the issue of digital rights management (DRM) has become increasingly important. DRM refers to the technological protection and control measures implemented by content creators to…

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