Topology-Aware Graph Pooling Networks

Graph Convolutional Networks with Argument-Aware Pooling for Event Detection

The current neural network models for event detection have only considered the sequential representation of sentences. Syntactic representations have not been explored in this area although they provide an effective mechanism to directly link words to their informative context for event detection in the sentences. In this work, we investigate a convolutional neural network based on dependency t...

Cost-aware Topology Customization of Mesh-based Networks-on-Chip

Nowadays, the growing demand for supporting multiple applications causes to use multiple IPs onto the chip. In fact, finding truly scalable communication architecture will be a critical concern. To this end, the Networks-on-Chip (NoC) paradigm has emerged as a promising solution to on-chip communication challenges within the silicon-based electronics. Many of today’s NoC architectures are based...

Topology adaptive graph convolutional networks

Convolution acts as a local feature extractor in convolutional neural networks (CNNs). However, the convolution operation is not applicable when the input data is supported on an irregular graph such as with social networks, citation networks, or knowledge graphs. This paper proposes the topology adaptive graph convolutional network (TAGCN), a novel graph convolutional network that generalizes ...

Algorithms for Topology-Aware Sensor Networks

Topology-Aware Overlay Construction in Dynamic Networks

Lately, peer-to-peer overlay networks and their ability to reflect the underlying network topology have been a focus in research. The main objective has been to reduce routing path lengths, stretched by the overlay routing process. In most solutions developed, a kind of fixed infrastructure in the form of so called landmarks or excessive message exchange are necessary to guarantee good overlay ...