David Arbour
David Arbour
Adobe Research
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Zitiert von
Zitiert von
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
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
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
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
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
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 App. 17/485,780, 2023
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