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09/13/2023
A Study of Symbiosis Bias in A/B Tests of Recommendation Algorithms
One assumption underlying the unbiasedness of global treatment effect es...
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08/02/2023
Causal Inference with Differentially Private (Clustered) Outcomes
Estimating causal effects from randomized experiments is only feasible i...
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06/01/2023
Causal Estimation of User Learning in Personalized Systems
In online platforms, the impact of a treatment on an observed outcome ma...
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05/18/2023
Modeling Interference Using Experiment Roll-out
Experiments on online marketplaces and social networks suffer from inter...
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10/28/2022
Cluster Randomized Designs for One-Sided Bipartite Experiments
The conclusions of randomized controlled trials may be biased when the o...
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03/18/2022
Optimizing Randomized and Deterministic Saturation Designs under Interference
Randomized saturation designs are a family of designs which assign a pos...
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12/01/2021
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls
We investigate the optimal design of experimental studies that have pre-...
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03/11/2021
Design and Analysis of Bipartite Experiments under a Linear Exposure-Response Model
The bipartite experimental framework is a recently proposed causal setti...
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10/05/2020
Causal Inference with Bipartite Designs
Bipartite experiments are a recent object of study in causal inference, ...
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03/07/2018
Optimizing cluster-based randomized experiments under a monotonicity assumption
Cluster-based randomized experiments are popular designs for mitigating ...
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05/21/2015
Inferring Graphs from Cascades: A Sparse Recovery Framework
In the Network Inference problem, one seeks to recover the edges of an u...
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09/03/2014
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
The authors of (Cho et al., 2014a) have shown that the recently introduc...
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06/10/2014