Information-Theoretic Caching: Sequential Coding for Computing

Sequential Feature Extraction Using Information-Theoretic Learning

A classification system typically includes both a feature extractor and a classifier. The two components can be trained either sequentially or simultaneously. The former option has an implementation advantage since the extractor is trained independently of the classifier, but it is hindered by the suboptimality of feature selection. Simultaneous training has the advantage of minimizing classifi...

Smart Collaborative Caching for Information-Centric IoT in Fog Computing

The significant changes enabled by the fog computing had demonstrated that Internet of Things (IoT) urgently needs more evolutional reforms. Limited by the inflexible design philosophy; the traditional structure of a network is hard to meet the latest demands. However, Information-Centric Networking (ICN) is a promising option to bridge and cover these enormous gaps. In this paper, a Smart Coll...

Sequential decoding for lossless streaming source coding with side information

The problem of lossless fixed-rate streaming coding of discrete memoryless sources with side information at the decoder is studied. A random time-varying tree-code is used to sequentially bin strings and a Stack Algorithm with a variable bias uses the side information to give a delay-universal coding system for lossless source coding with side information. The scheme is shown to give exponentia...

Coding and Information-Theoretic Aspects of Multiple Antenna Communication Systems

Generalized ACE Codes and Information Theoretic Results in Network Coding

of the Dissertation Generalized ACE Codes and Information Theoretic Results in Network Coding