Arbour, David

20 publications

AAAI 2025 Evaluation and Incident Prevention in an Enterprise AI Assistant Akash V. Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup B. Rao, Austin Zane, Avi Feller, Kun Qian, Yunyao Li

NeurIPS 2025 Handling Missing Responses Under Cluster Dependence with Applications to Language Model Evaluation Zhenghao Zeng, David Arbour, Avi Feller, Ishita Dasgupta, Atanu R. Sinha, Edward Kennedy

NeurIPS 2025 Leveraging Semantic Similarity for Experimentation with AI-Generated Treatments Lei Shi, David Arbour, Raghavendra Addanki, Ritwik Sinha, Avi Feller

UAI 2025 Relational Causal Discovery with Latent Confounders Matteo Negro, Andrea Piras, Ragib Ahsan, David Arbour, Elena Zheleva

ICML 2024 Continuous Treatment Effects with Surrogate Outcomes Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward Kennedy

AAAI 2024 Distributional Off-Policy Evaluation for Slate Recommendations Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis

ICML 2024 Editing Partially Observable Networks via Graph Diffusion Models Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra

NeurIPS 2023 Finite Population Regression Adjustment and Non-Asymptotic Guarantees for Treatment Effect Estimation Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao

AAAI 2023 Learning Relational Causal Models with Cycles Through Relational Acyclification Ragib Ahsan, David Arbour, Elena Zheleva

AAAI 2022 Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill

WACV 2022 Generating and Controlling Diversity in Image Search Md. Mehrab Tanjim, Ritwik Sinha, Krishna Kumar Singh, Sridhar Mahadevan, David Arbour, Moumita Sinha, Garrison W. Cottrell

UAI 2022 Non-Parametric Inference of Relational Dependence Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva

ICML 2022 Online Balanced Experimental Design David Arbour, Drew Dimmery, Tung Mai, Anup Rao

CLeaR 2022 Relational Causal Models with Cycles: Representation and Reasoning Ragib Ahsan, David Arbour, Elena Zheleva

NeurIPS 2022 Sample Constrained Treatment Effect Estimation Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao

AISTATS 2021 Designing Transportable Experiments Under S-Admissability My Phan, David Arbour, Drew Dimmery, Anup Rao

AISTATS 2021 Efficient Balanced Treatment Assignments for Experimentation David Arbour, Drew Dimmery, Anup Rao

ICML 2021 Permutation Weighting David Arbour, Drew Dimmery, Arjun Sondhi

AISTATS 2020 Balanced Off-Policy Evaluation in General Action Spaces Arjun Sondhi, David Arbour, Drew Dimmery

AISTATS 2020 General Identification of Dynamic Treatment Regimes Under Interference Eli Sherman, David Arbour, Ilya Shpitser