75 citations · 92 across the 11 of their papers we have counts for
16 papers
Sub-Graph Learning for Spatiotemporal Forecasting via Knowledge Distillation
Mehrtash Mehrabi, Yingxue Zhang
One of the challenges in studying the interactions in large graphs is to learn their diverse pattern and various interaction types. Hence, considering only one distribution and mod…
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang +1
Spatio-temporal forecasting has numerous applications in analyzing wireless, traffic, and financial networks. Many classical statistical models often fall short in handling the com…
Dual Graph enhanced Embedding Neural Network for CTR Prediction
Wei Guo, Rong Su, Renhao Tan +5
CTR prediction, which aims to estimate the probability that a user will click an item, plays a crucial role in online advertising and recommender system. Feature interaction modeli…
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
Jiapeng Wu, Yishi Xu, Yingxue Zhang +3
Reasoning in a temporal knowledge graph (TKG) is a critical task for information retrieval and semantic search. It is particularly challenging when the TKG is updated frequently. T…
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball
Chen Ma, Liheng Ma, Yingxue Zhang +3
Personalized recommender systems are increasingly important as more content and services become available and users struggle to identify what might interest them. Thanks to the abi…
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation
Chen Ma, Liheng Ma, Yingxue Zhang +3
Personalized recommender systems are playing an increasingly important role as more content and services become available and users struggle to identify what might interest them. A…