David Arbour
David Arbour
Adobe Research
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Cited by
Cited by
A sound and complete algorithm for learning causal models from relational data
M Maier, K Marazopoulou, D Arbour, D Jensen
arXiv preprint arXiv:1309.6843, 2013
Time-uniform central limit theory, asymptotic confidence sequences, and anytime-valid causal inference
I Waudby-Smith, D Arbour, R Sinha, EH Kennedy, A Ramdas
arXiv preprint arXiv:2103.06476 11, 2021
Inferring Network Effects from Observational Data
D Arbour, D Garant, D Jensen
KDD, 2016
Heterogeneous network motifs
RA Rossi, NK Ahmed, A Carranza, D Arbour, A Rao, S Kim, E Koh
arXiv preprint arXiv:1901.10026, 2019
Permutation weighting
D Arbour, D Dimmery, A Sondhi
International Conference on Machine Learning, 331-341, 2021
Heterogeneous graphlets
RA Rossi, NK Ahmed, A Carranza, D Arbour, A Rao, S Kim, E Koh
ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (1), 1-43, 2020
Balanced off-policy evaluation in general action spaces
A Sondhi, D Arbour, D Dimmery
International Conference on Artificial Intelligence and Statistics, 2413-2423, 2020
Adjusting for confounders with text: Challenges and an empirical evaluation framework for causal inference
G Weld, P West, M Glenski, D Arbour, RA Rossi, T Althoff
Proceedings of the international AAAI conference on web and social media 16 …, 2022
Propensity Score Matching for Causal Inference with Relational Data.
DT Arbour, K Marazopoulou, D Garant, DD Jensen
CI@ UAI, 25-34, 2014
First experiences with a classroom recording system
PE Dickson, WR Adrion, AR Hanson, DT Arbour
Proceedings of the 14th annual ACM SIGCSE conference on Innovation and …, 2009
Estimating the effects of a California gun control program with multitask Gaussian processes
E Ben-Michael, D Arbour, A Feller, A Franks, S Raphael
The Annals of Applied Statistics 17 (2), 985-1016, 2023
General identification of dynamic treatment regimes under interference
E Sherman, D Arbour, I Shpitser
International Conference on Artificial Intelligence and Statistics, 3917-3927, 2020
Anytime-valid confidence sequences in an enterprise a/b testing platform
A Maharaj, R Sinha, D Arbour, I Waudby-Smith, SZ Liu, M Sinha, ...
Companion Proceedings of the ACM Web Conference 2023, 396-400, 2023
Causal inference from network data
E Zheleva, D Arbour
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
Evaluation of automatic classroom capture for computer science education
PE Dickson, DT Arbour, WR Adrion, A Gentzel
Proceedings of the fifteenth annual conference on Innovation and technology …, 2010
Generating and controlling diversity in image search
MM Tanjim, R Sinha, KK Singh, S Mahadevan, D Arbour, M Sinha, ...
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
Constraint sampling reinforcement learning: Incorporating expertise for faster learning
T Mu, G Theocharous, D Arbour, E Brunskill
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7841-7849, 2022
Efficient balanced treatment assignments for experimentation
D Arbour, D Dimmery, A Rao
International Conference on Artificial Intelligence and Statistics, 3070-3078, 2021
Inferring Causal Direction from Relational Data
D Arbour, K Marazopoulou, D Jensen
Uncertainty in Artificial Intelligence, 2016
Generating simulated images that enhance socio-demographic diversity
R Sinha, S Mahadevan, M Sinha, MM Tanjim, KK Singh, D Arbour
US Patent 12,001,520, 2024
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