Search Results for author:
Found 7 papers, 2 papers with code
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation
Users influential in the propagation of true and fake contents are identified using the inferred diffusion dynamics.
DynGEM: Deep Embedding Method for Dynamic Graphs
The major advantages of DynGEM include: (1) the embedding is stable over time, (2) it can handle growing dynamic graphs, and (3) it has better running time than using static embedding methods on each snapshot of a dynamic graph.
Social and Information Networks
mvn2vec: Preservation and Collaboration in Multi-View Network Embedding
With experiments on a series of synthetic datasets, a large-scale internal Snapchat dataset, and two public datasets, we confirm the validity and importance of preservation and collaboration as two objectives for multi-view network embedding.
Learning Influence Functions from Incomplete Observations
We establish both proper and improper PAC learnability of influence functions under randomly missing observations.
Learning and Optimization with Submodular Functions
Set functions, and specifically submodular set functions, characterize a wide variety of naturally occurring optimization problems, and the property of submodularity of set functions has deep theoretical consequences with wide ranging applications.
Model Selection for Topic Models via Spectral Decomposition
Topic models have achieved significant successes in analyzing large-scale text corpus.
GLAD: Group Anomaly Detection in Social Media Analysis- Extended Abstract
Existing group anomaly detection approaches rely on the assumption that the groups are known, which can hardly be true in real world social media applications.
