2.4k citations · 3.4k across the 27 of their papers we have counts for
6 papers · 1 filter
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
Ruocheng Guo, Jundong Li, Huan Liu
Counterfactual evaluation of novel treatment assignment functions (e.g., advertising algorithms and recommender systems) is one of the most crucial causal inference problems for pr…
Generating Reliable Friends via Adversarial Training to Improve Social Recommendation
Junliang Yu, Min Gao, Hongzhi Yin +3
Most of the recent studies of social recommendation assume that people share similar preferences with their friends and the online social relations are helpful in improving traditi…
Deep Structured Cross-Modal Anomaly Detection
Yuening Li, Ninghao Liu, Jundong Li +2
Anomaly detection is a fundamental problem in data mining field with many real-world applications. A vast majority of existing anomaly detection methods predominately focused on da…
Feature Interaction-aware Graph Neural Networks
Kaize Ding, Yichuan Li, Jundong Li +2
Inspired by the immense success of deep learning, graph neural networks (GNNs) are widely used to learn powerful node representations and have demonstrated promising performance on…
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks
Yuening Li, Xiao Huang, Jundong Li +2
Anomaly detection aims to distinguish observations that are rare and different from the majority. While most existing algorithms assume that instances are i.i.d., in many practical…
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
Yuxin Ma, Tiankai Xie, Jundong Li +1
Machine learning models are currently being deployed in a variety of real-world applications where model predictions are used to make decisions about healthcare, bank loans, and nu…