
Doubly robust confidence sequences for sequential causal inference
This paper derives timeuniform confidence sequences (CS) for causal eff...
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Online Discrepancy Minimization via Persistent SelfBalancing Walks
We study the online discrepancy minimization problem for vectors in ℝ^d ...
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Heterogeneous Graphlets
In this paper, we introduce a generalization of graphlets to heterogeneo...
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Efficient Balanced Treatment Assignments for Experimentation
In this work, we reframe the problem of balanced treatment assignment as...
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Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference
Leveraging text, such as social media posts, for causal inferences requi...
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Designing Transportable Experiments
We consider the problem of designing a randomized experiment on a source...
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General Identification of Dynamic Treatment Regimes Under Interference
In many applied fields, researchers are often interested in tailoring tr...
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Inferring Individual Level Causal Models from Graphbased Relational Time Series
In this work, we formalize the problem of causal inference over graphba...
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Balanced OffPolicy Evaluation in General Action Spaces
In many practical applications of contextual bandits, online learning is...
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Balanced OffPolicy Evaluation General Action Spaces
In many practical applications of contextual bandits, online learning is...
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Heterogeneous Network Motifs
Many realworld applications give rise to large heterogeneous networks w...
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Permutation Weighting
This work introduces permutation weighting: a weighting estimator for ob...
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A Sound and Complete Algorithm for Learning Causal Models from Relational Data
The PC algorithm learns maximally oriented causal Bayesian networks. How...
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David Arbour
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