49 citations · 263 across the 36 of their papers we have counts for
6 papers · 1 filter
Heterogeneous Graphlets
Ryan A. Rossi, Nesreen K. Ahmed, Aldo Carranza +4
In this paper, we introduce a generalization of graphlets to heterogeneous networks called typed graphlets. Informally, typed graphlets are small typed induced subgraphs. Typed gra…
Efficient Balanced Treatment Assignments for Experimentation
David Arbour, Drew Dimmery, Anup Rao
In this work, we reframe the problem of balanced treatment assignment as optimization of a two-sample test between test and control units. Using this lens we provide an assignment…
Graph Neural Networks with Heterophily
Jiong Zhu, Ryan A. Rossi, Anup Rao +4
Graph Neural Networks (GNNs) have proven to be useful for many different practical applications. However, many existing GNN models have implicitly assumed homophily among the nodes…
Designing Transportable Experiments
My Phan, David Arbour, Drew Dimmery +1
We consider the problem of designing a randomized experiment on a source population to estimate the Average Treatment Effect (ATE) on a target population. We propose a novel approa…
Sample Efficient Graph-Based Optimization with Noisy Observations
Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori +2
We study sample complexity of optimizing "hill-climbing friendly" functions defined on a graph under noisy observations. We define a notion of convexity, and we show that a variant…
Model Selection in Contextual Stochastic Bandit Problems
Aldo Pacchiano, My Phan, Yasin Abbasi-Yadkori +4
We study bandit model selection in stochastic environments. Our approach relies on a meta-algorithm that selects between candidate base algorithms. We develop a meta-algorithm-base…