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Jean Pouget-Abadie
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2020 – today
- 2024
- [c14]Zahra Fatemi, Jean Pouget-Abadie, Elena Zheleva:
Cascade-Based Randomization for Inferring Causal Effects under Diffusion Interference. ICWSM 2024: 394-407 - [i6]Zahra Fatemi, Jean Pouget-Abadie, Elena Zheleva:
Cascade-based Randomization for Inferring Causal Effects under Diffusion Interference. CoRR abs/2405.12340 (2024) - 2023
- [c13]Ariel Boyarsky, Hongseok Namkoong, Jean Pouget-Abadie:
Modeling Interference Using Experiment Roll-out. EC 2023: 298 - [c12]Evan Munro, David Jones, Jennifer Brennan, Roland Nelet, Vahab Mirrokni, Jean Pouget-Abadie:
Causal Estimation of User Learning in Personalized Systems. EC 2023: 992-1016 - [i5]Evan Munro, David Jones, Jennifer Brennan, Roland Nelet, Vahab Mirrokni, Jean Pouget-Abadie:
Causal Estimation of User Learning in Personalized Systems. CoRR abs/2306.00485 (2023) - [i4]Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie:
Causal Inference with Differentially Private (Clustered) Outcomes. CoRR abs/2308.00957 (2023) - 2022
- [c11]Jennifer Brennan, Vahab Mirrokni, Jean Pouget-Abadie:
Cluster Randomized Designs for One-Sided Bipartite Experiments. NeurIPS 2022 - [c10]Christopher Harshaw, Fredrik Sävje, David Eisenstat, Vahab Mirrokni, Jean Pouget-Abadie:
Design and Analysis of Bipartite Experiments Under a Linear Exposure-response Model. EC 2022: 606 - 2021
- [c9]Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sébastien Lahaie, Miles Lubin, Vahab S. Mirrokni, Jann Spiess, Guido Imbens:
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls. NeurIPS 2021: 8691-8701 - 2020
- [j1]Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio:
Generative adversarial networks. Commun. ACM 63(11): 139-144 (2020)
2010 – 2019
- 2019
- [c8]David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab S. Mirrokni, Amir Najmi:
Randomized Experimental Design via Geographic Clustering. KDD 2019: 2745-2753 - [c7]Jean Pouget-Abadie, Kevin Aydin, Warren Schudy, Kay Brodersen, Vahab S. Mirrokni:
Variance Reduction in Bipartite Experiments through Correlation Clustering. NeurIPS 2019: 13288-13298 - 2018
- [c6]Jean Pouget-Abadie, Vahab S. Mirrokni, David C. Parkes, Edoardo M. Airoldi:
Optimizing Cluster-based Randomized Experiments under Monotonicity. KDD 2018: 2090-2099 - 2017
- [c5]Martin Saveski, Jean Pouget-Abadie, Guillaume Saint-Jacques, Weitao Duan, Souvik Ghosh, Ya Xu, Edoardo M. Airoldi:
Detecting Network Effects: Randomizing Over Randomized Experiments. KDD 2017: 1027-1035 - 2015
- [c4]Jean Pouget-Abadie, Thibaut Horel:
Inferring Graphs from Cascades: A Sparse Recovery Framework. ICML 2015: 977-986 - [c3]Jean Pouget-Abadie, Thibaut Horel:
Inferring Graphs from Cascades: A Sparse Recovery Framework. WWW (Companion Volume) 2015: 625-626 - [i3]Jean Pouget-Abadie, Thibaut Horel:
Inferring Graphs from Cascades: A Sparse Recovery Framework. CoRR abs/1505.05663 (2015) - 2014
- [c2]Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio:
Generative Adversarial Nets. NIPS 2014: 2672-2680 - [c1]Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer, Kyunghyun Cho, Yoshua Bengio:
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation. SSST@EMNLP 2014: 78-85 - [i2]Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio:
Generative Adversarial Networks. CoRR abs/1406.2661 (2014) - [i1]Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer, KyungHyun Cho, Yoshua Bengio:
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation. CoRR abs/1409.1257 (2014)
Coauthor Index
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