6 papers
Support Estimation with Sampling Artifacts and Errors
Eli Chien, Olgica Milenkovic, Angelia Nedich
The problem of estimating the support of a distribution is of great importance in many areas of machine learning, computer science, physics and biology. Most of the existing work i…
Active learning in the geometric block model
Eli Chien, Antonia Maria Tulino, Jaime Llorca
The geometric block model is a recently proposed generative model for random graphs that is able to capture the inherent geometric properties of many community detection problems,…
Multi-MotifGAN (MMGAN): Motif-targeted Graph Generation and Prediction
Anuththari Gamage, Eli Chien, Jianhao Peng +1
Generative graph models create instances of graphs that mimic the properties of real-world networks. Generative models are successful at retaining pairwise associations in the unde…
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection
Pan Li, Eli Chien, Olgica Milenkovic
Landing probabilities (LP) of random walks (RW) over graphs encode rich information regarding graph topology. Generalized PageRanks (GPR), which represent weighted sums of LPs of R…
Regularized Weighted Chebyshev Approximations for Support Estimation
I, Chien, Olgica Milenkovic
We introduce a new method for estimating the support size of an unknown distribution which provably matches the performance bounds of the state-of-the-art techniques in the area an…
: Active Learning over Hypergraphs
I Chien, Huozhi Zhou, Pan Li
We propose a hypergraph-based active learning scheme which we term , generalizes the previously reported algorithm originally proposed for graph-based active lea…