[ad_1] Introduction Privacy-preserving smart contracts have gained significant attention in recent years due to the growing concern over data privacy and security in decentralized applications. Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as…
Read More
[ad_1] Introduction: Quantum machine learning is a relatively new and exciting field that combines aspects of quantum mechanics and machine learning to solve complex problems in various domains. In recent years, quantum machine learning has…
Read More
[ad_1] Introduction: Decentralized online marketplaces have revolutionized traditional ways of conducting commerce by leveraging blockchain technology. This thesis aims to explore the potential of decentralized online marketplaces using blockchain to enhance security, transparency, and efficiency…
Read More
[ad_1] Introduction In recent years, the field of quantum computing has gained increasing attention for its potential to revolutionize traditional optimization techniques. Quantum-inspired optimization algorithms, which draw inspiration from the principles of quantum mechanics, have…
Read More
[ad_1] Introduction In recent years, machine learning has become increasingly popular in various domains such as e-commerce, healthcare, and finance. One application of machine learning that has gained significant interest is recommendation systems, which aim…
Read More
[ad_1] Introduction In the era of big data, the need for sharing and publishing data while protecting individual privacy has become increasingly important. Differential privacy has emerged as a prominent framework for achieving this balance…
Read More
[ad_1] Introduction Quantum communication has the potential to revolutionize the way we transmit and process information by taking advantage of the unique properties of quantum mechanics. However, quantum systems are inherently susceptible to errors due…
Read More
[ad_1] Introduction: Protein-protein interactions play a crucial role in various cellular processes and diseases. Understanding the intricate interactions between proteins is essential for drug discovery, disease diagnosis, and treatment. Graph neural networks (GNNs) have emerged…
Read More
[ad_1] Introduction: Transfer learning has emerged as a powerful technique in the field of machine learning, allowing models trained on one task or dataset to be adapted to perform well on another task or dataset.…
Read More
[ad_1] Introduction Homomorphic encryption is a revolutionary technology that allows for computations to be performed on encrypted data without decrypting it. This provides a secure way to outsource data storage and processing to third-party servers…
Read More