This special issue will focus on exploring the intersection of privacy and security with information and coding theory, as well as applications in communication theory, cryptography, computer science, machine learning, and hardware security.Â
This special issue will focus on the intersection of Information theory with estimation and inference. Information Theory has provided powerful tools as well as deep insights into optimal procedures for statistical inference and estimation. The application of these tools include characterization of optimal error probabilities in hypothesis testing, determination of minimax rates of convergence for estimation problems, analysis of message-passing and other efficient algorithms, as well as demonstrating the equivalence of different estimation problems. This issue will illuminate new connections between information theory, statistical inference, and estimation, as well as highlight applications where information-theoretic tools for inference and estimation have proved fruitful in a wide range of areas including signal processing, data mining, machine learning, pattern and image recognition, computational neuroscience, bioinformatics and cryptography.
This special issue will focus on Quantum Information Science, especially Communication and Computing. It will aim to bridge theory, practice and basic science, ranging from the state-of-the-art in quantum computing, to communication, coding, cryptography, and compression, as well as the current challenges remaining. An overarching theme is how the information-theoretic and quantum-physical perspectives complement each other in building these quantum technologies.
JSAIT's first special issue will focus on the mathematical foundations of deep learning as well as applications across information science.