19 citations · 27 across the 4 of their papers we have counts for
4 papers
Landmarks and Regions: A Robust Approach to Data Extraction
Suresh Parthasarathy, Lincy Pattanaik, Anirudh Khatry +4
We propose a new approach to extracting data items or field values from semi-structured documents. Examples of such problems include extracting passenger name, departure time and d…
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs
Vijay Lingam, Rahul Ragesh, Arun Iyer +1
Graph Neural Networks (GNNs) have shown excellent performance on graphs that exhibit strong homophily with respect to the node labels i.e. connected nodes have same labels. However…
GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks
Vijay Lingam, Arun Iyer, Rahul Ragesh
Graph Neural Networks have shown excellent performance on semi-supervised classification tasks. However, they assume access to a graph that may not be often available in practice.…
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer +2
We consider the problem of learning efficient and inductive graph convolutional networks for text classification with a large number of examples and features. Existing state-of-the…