223 citations · 758 across the 42 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…
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning
Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo +3
Recommendation is one of the critical applications that helps users find information relevant to their interests. However, a malicious attacker can infer users' private information…
I Am Not What I Write: Privacy Preserving Text Representation Learning
Ghazaleh Beigi, Kai Shu, Ruocheng Guo +2
Online users generate tremendous amounts of textual information by participating in different activities, such as writing reviews and sharing tweets. This textual data provides opp…
Learning Individual Causal Effects from Networked Observational Data
Ruocheng Guo, Jundong Li, Huan Liu
Convenient access to observational data enables us to learn causal effects without randomized experiments. This research direction draws increasing attention in research areas such…
Detecting Pathogenic Social Media Accounts without Content or Network Structure
Elham Shaabani, Ruocheng Guo, Paulo Shakarian
The spread of harmful mis-information in social media is a pressing problem. We refer accounts that have the capability of spreading such information to viral proportions as "Patho…
Using network motifs to characterize temporal network evolution leading to diffusion inhibition
Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian
Network motifs are patterns of over-represented node interactions in a network which have been previously used as building blocks to understand various aspects of the social networ…