5 citations · 11 across the 3 of their papers we have counts for
3 papers
cs.IR2022★ 3 cited
ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest
Paul Baltescu, Haoyu Chen, Nikil Pancha +3
Learned embeddings for products are an important building block for web-scale e-commerce recommendation systems. At Pinterest, we build a single set of product embeddings called It…
cs.LG2022★ 5 cited
MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest
Saket Gurukar, Nikil Pancha, Andrew Zhai +5
Graph Convolutional Networks (GCN) can efficiently integrate graph structure and node features to learn high-quality node embeddings. These embeddings can then be used for several…
cs.LG2022★ 3 cited
PinnerFormer: Sequence Modeling for User Representation at Pinterest
Nikil Pancha, Andrew Zhai, Jure Leskovec +1
Sequential models have become increasingly popular in powering personalized recommendation systems over the past several years. These approaches traditionally model a user's action…