72 citations · 158 across the 8 of their papers we have counts for
6 papers · 1 filter
On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs
Behzad Shahrasbi, Venugopal Mani, Apoorv Reddy Arrabothu +3
Recommender systems are an essential part of any e-commerce platform. Recommendations are typically generated by aggregating large amounts of user data. A malicious actor may be mo…
On Variational Inference for User Modeling in Attribute-Driven Collaborative Filtering
Venugopal Mani, Ramasubramanian Balasubramanian, Sushant Kumar +2
Recommender Systems have become an integral part of online e-Commerce platforms, driving customer engagement and revenue. Most popular recommender systems attempt to learn from use…
Inductive Representation Learning on Temporal Graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
Inductive representation learning on temporal graphs is an important step toward salable machine learning on real-world dynamic networks. The evolving nature of temporal dynamic gr…
Self-attention with Functional Time Representation Learning
Da Xu, Chuanwei Ruan, Sushant Kumar +2
Sequential modelling with self-attention has achieved cutting edge performances in natural language processing. With advantages in model flexibility, computation complexity and int…
Product Knowledge Graph Embedding for E-commerce
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
In this paper, we propose a new product knowledge graph (PKG) embedding approach for learning the intrinsic product relations as product knowledge for e-commerce. We define the key…
Generative Graph Convolutional Network for Growing Graphs
Da Xu, Chuanwei Ruan, Kamiya Motwani +3
Modeling generative process of growing graphs has wide applications in social networks and recommendation systems, where cold start problem leads to new nodes isolated from existin…