5 citations · 7 across the 5 of their papers we have counts for
5 papers
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce
Nurendra Choudhary, Edward W Huang, Karthik Subbian +1
The problem of search relevance in the E-commerce domain is a challenging one since it involves understanding the intent of a user's short nuanced query and matching it with the ap…
ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding
Zixuan Liu, Gaurush Hiranandani, Kun Qian +5
Developing text mining approaches to mine aspects from customer reviews has been well-studied due to its importance in understanding customer needs and product attributes. In contr…
Communication-Free Distributed GNN Training with Vertex Cut
Kaidi Cao, Rui Deng, Shirley Wu +3
Training Graph Neural Networks (GNNs) on real-world graphs consisting of billions of nodes and edges is quite challenging, primarily due to the substantial memory needed to store t…
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
Jiong Zhu, Aishwarya Reganti, Edward Huang +4
Distributed training of GNNs enables learning on massive graphs (e.g., social and e-commerce networks) that exceed the storage and computational capacity of a single machine. To re…
Text Enriched Sparse Hyperbolic Graph Convolutional Networks
Nurendra Choudhary, Nikhil Rao, Karthik Subbian +1
Heterogeneous networks, which connect informative nodes containing text with different edge types, are routinely used to store and process information in various real-world applica…