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Design and Analysis of Bipartite Experiments under a Linear
  Exposure-Response Model

Design and Analysis of Bipartite Experiments under a Linear Exposure-Response Model

11 March 2021
Christopher Harshaw
Fredrik Sävje
David Eisenstat
Vahab Mirrokni
Jean Pouget-Abadie
ArXivPDFHTML

Papers citing "Design and Analysis of Bipartite Experiments under a Linear Exposure-Response Model"

12 / 12 papers shown
Title
Higher-Order Causal Message Passing for Experimentation with Complex Interference
Higher-Order Causal Message Passing for Experimentation with Complex Interference
Mohsen Bayati
Yuwei Luo
William Overman
Sadegh Shirani
Ruoxuan Xiong
32
0
0
01 Nov 2024
Some theoretical foundations for the design and analysis of randomized
  experiments
Some theoretical foundations for the design and analysis of randomized experiments
Lei Shi
Xinran Li
18
1
0
14 Jun 2024
Cascade-based Randomization for Inferring Causal Effects under Diffusion
  Interference
Cascade-based Randomization for Inferring Causal Effects under Diffusion Interference
Zahra Fatemi
Jean Pouget-Abadie
Elena Zheleva
CML
29
0
0
20 May 2024
Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
Luofeng Liao
Christian Kroer
Sergei Leonenkov
Okke Schrijvers
Liang Shi
Nicolas Stier-Moses
Congshan Zhang
25
2
0
11 Feb 2024
Individualized Policy Evaluation and Learning under Clustered Network Interference
Individualized Policy Evaluation and Learning under Clustered Network Interference
Yi Zhang
Kosuke Imai
OffRL
34
1
0
04 Nov 2023
Tackling Interference Induced by Data Training Loops in A/B Tests: A
  Weighted Training Approach
Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach
Nian Si
11
4
0
26 Oct 2023
A Two-Part Machine Learning Approach to Characterizing Network
  Interference in A/B Testing
A Two-Part Machine Learning Approach to Characterizing Network Interference in A/B Testing
Yuan. Yuan
Kristen M. Altenburger
21
4
0
18 Aug 2023
Causal Estimation of User Learning in Personalized Systems
Causal Estimation of User Learning in Personalized Systems
Evan Munro
David Jones
Jennifer Brennan
Roland Nelet
Vahab Mirrokni
Jean Pouget-Abadie
CML
18
2
0
01 Jun 2023
A Design-Based Riesz Representation Framework for Randomized Experiments
A Design-Based Riesz Representation Framework for Randomized Experiments
Christopher Harshaw
Fredrik Sävje
Yitan Wang
CML
22
7
0
17 Oct 2022
Asymptotic Causal Inference
Asymptotic Causal Inference
Sridhar Mahadevan
CML
19
2
0
20 Sep 2021
Treatment Allocation with Strategic Agents
Treatment Allocation with Strategic Agents
Evan Munro
13
6
0
12 Nov 2020
Causal Inference in the Presence of Interference in Sponsored Search
  Advertising
Causal Inference in the Presence of Interference in Sponsored Search Advertising
Razieh Nabi
Joel Pfeiffer
Murat Ali Bayir
Denis Xavier Charles
Emre Kıcıman
CML
18
14
0
15 Oct 2020
1