These include networks with multiple transmitters, multiple receivers, decoder side information, intermediate nodes, and any combination of these features.
In the context of the setting discussed in this article, the index coding problem [17], which also considers only a single sender with multiple receivers (having side information), is also unsolved in general.
Owing to the main FSVQ which effectively exploits the inter-frame dependencies, the source sequence is split into multiple clusters and no side information is needed to be transmitted.
By leveraging available information from multiple side views together with graph data, the proposed method gMSV can achieve very good performance on the problem of feature selection for graph classification, and the selected subgraph patterns are relevant to disease diagnosis.
In this paper, we explore the side information from multiple views to effectively facilitate the procedure of discriminative subgraph mining.
Multiple description coding (MDC) with side information (SI) at the receiver is particularly relevant for robust transmission in sensor networks where correlated data is being transmitted to a common receiver, as well as for robust video compression.
Our method operates in similar philosophy as spatial audio coding, that is, it reduces a multichannel recording into a single audio channel (which can be a sum of the multiple microphone signals) and some side information of the order of few kbps per channel.
How to leverage the valuable information embedded in multiple side views to evaluate the usefulness of a set of subgraph patterns?
This is non-trivial due to the following problems: How to leverage the valuable information embedded in multiple side views to evaluate the usefulness of a set of subgraph patterns?
The focus of this paper is to investigate side information consistency and explore multiple side views in discriminative subgraph selection.
