13 citations · 17 across the 8 of their papers we have counts for
9 papers
Flurry: a Fast Framework for Reproducible Multi-layered Provenance Graph Representation Learning
Maya Kapoor, Joshua Melton, Michael Ridenhour +3
Complex heterogeneous dynamic networks like knowledge graphs are powerful constructs that can be used in modeling data provenance from computer systems. From a security perspective…
Pay Attention to Relations: Multi-embeddings for Attributed Multiplex Networks
Joshua Melton, Michael Ridenhour, Siddharth Krishnan
Graph Convolutional Neural Networks (GCNs) have become effective machine learning algorithms for many downstream network mining tasks such as node classification, link prediction,…
A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches
Prasad hajare, Sadia Kamal, Siddharth Krishnan +1
Computational methods to model political bias in social media involve several challenges due to heterogeneity, high-dimensional, multiple modalities, and the scale of the data. Pol…
DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech Detection
Joshua Melton, Arunkumar Bagavathi, Siddharth Krishnan
Online hate speech on social media has become a fast-growing problem in recent times. Nefarious groups have developed large content delivery networks across several main-stream (Tw…
Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models
Michael Ridenhour, Arunkumar Bagavathi, Elaheh Raisi +1
The ubiquity of social media has transformed online interactions among individuals. Despite positive effects, it has also allowed anti-social elements to unite in alternative socia…
ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music Concert
Arunkumar Bagavathi, Siddharth Krishnan, Sanjay Subrahmanyan +1
South Indian classical music (Carnatic music) is best consumed through live concerts. A carnatic recital requires meticulous planning accounting for several parameters like the per…