IIITH faculty and students presented the following papers at the 2020 IEEE International Symposium on Information Theory (ISIT) held in virtual mode from 21 – 26 June at Los Angeles, USA.
- Low Complexity Distributed Computing via Binary Matrices with Extension to Stragglers – Shailja Agrawal, Prasad Krishnan
- Coded Data Rebalancing: Fundamental Limits and Constructions – Prasad Krishnan, Lalitha Vadlamani, Lakshmi Natarajan.
ISIT is a premier international conference dedicated to the advancement of information theory and related areas. It brings together an international community of researchers and practitioners each year in the field of information theory to present and discuss new research results and perspectives on future developments relevant to all areas of information theory, including big data analytics, source and channel coding, communication theory and systems, cryptography and security, detection and estimation, emerging applications, networks, network coding/information theory, signal processing, and statistical/machine learning.
Hosted by the IEEE Information Theory Society, the 2020 ISIT featured contributed papers, the Shannon lecture and plenary talks, as well as tutorial sessions. ISIT is the flagship conference of the IEEE Information Theory Society.