David Arbour - RankMe

53 papers A* 13A 8B 3C 1Journal 24Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Experimentation Accelerator: Interpretable Insights and Creative Recommendations for A/B Testing with Content-Aware ranking. CoRR Zhengmian Hu, Lei Shi, Ritwik Sinha, Justin Grover, David Arbour
2025	A*	`conf`	Evaluation and Incident Prevention in an Enterprise AI Assistant. AAAI Akash V. Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup B. Rao, Austin Zane, Avi Feller, Kun Qian, Yunyao Li
2025	J	`jnl`	Evaluation and Incident Prevention in an Enterprise AI Assistant. CoRR Akash V. Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup B. Rao, Austin Zane, Avi Feller, Kun Qian, Yunyao Li
2025	J	`jnl`	Evaluation and incident prevention in an enterprise AI assistant. AI Mag. Akash V. Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup Rao, Austin Zane, Avi Feller, Kun Qian, Sajjadur Rahman, Yunyao Li
2025	A*	`conf`	Image Difference Captioning via Adversarial Preference Optimization. EMNLP Zihan Huang, Junda Wu, Rohan Surana, Tong Yu, David Arbour, Ritwik Sinha, Julian J. McAuley
2025	—	`conf`	Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries. ACL (1) Vishakh Padmakumar, Zichao Wang, David Arbour, Jennifer Healey
2025	J	`jnl`	Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries. CoRR Vishakh Padmakumar, Zichao Wang, David Arbour, Jennifer Healey
2025	J	`jnl`	Regularizing Extrapolation in Causal Inference. CoRR David Arbour, Harsh Parikh, Bijan Niknam, Elizabeth A. Stuart, Kara E. Rudolph, Avi Feller
2025	A	`conf`	Relational Causal Discovery with Latent Confounders. UAI Matteo Negro, Andrea Piras, Ragib Ahsan, David Arbour, Elena Zheleva
2025	J	`jnl`	Relational Causal Discovery with Latent Confounders. CoRR Andrea Piras, Matteo Negro, Ragib Ahsan, David Arbour, Elena Zheleva
2025	J	`jnl`	Think Global, Act Local: Bayesian Causal Discovery with Language Models in Sequential Data. CoRR Prakhar Verma, David Arbour, Sunav Choudhary, Harshita Chopra, Arno Solin, Atanu R. Sinha
2024	A*	`conf`	Continuous Treatment Effects with Surrogate Outcomes. ICML Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward H. Kennedy
2024	J	`jnl`	Continuous Treatment Effects with Surrogate Outcomes. CoRR Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward H. Kennedy
2024	A*	`conf`	Distributional Off-Policy Evaluation for Slate Recommendations. AAAI Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis
2024	A*	`conf`	Editing Partially Observable Networks via Graph Diffusion Models. ICML Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
2023	—	`conf`	Anytime-Valid Confidence Sequences in an Enterprise A/B Testing Platform. WWW (Companion Volume) Akash Maharaj, Ritwik Sinha, David Arbour, Ian Waudby-Smith, Simon Z. Liu, Moumita Sinha, Raghavendra Addanki, Aaditya Ramdas, Manas Garg, Viswanathan Swaminathan
2023	B	`conf`	Brief Announcement: Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. SPAA Aniket Murhekar, David Arbour, Tung Mai, Anup B. Rao
2023	J	`jnl`	Distributional Off-Policy Evaluation for Slate Recommendations. CoRR Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis
2023	J	`jnl`	Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. CoRR Aniket Murhekar, David Arbour, Tung Mai, Anup Rao
2023	A*	`conf`	Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. NeurIPS Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao
2023	A*	`conf`	Learning Relational Causal Models with Cycles through Relational Acyclification. AAAI Ragib Ahsan, David Arbour, Elena Zheleva
2023	J	`jnl`	Leveraging Graph Diffusion Models for Network Refinement Tasks. CoRR Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
2023	B	`conf`	Online Forecasting Based Anomaly Detection For Monitoring Large Scale Streaming Data. IEEE Big Data Wei Zhang, David Arbour
2022	A	`conf`	Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference. ICWSM Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan A. Rossi, Tim Althoff
2022	A*	`conf`	Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning. AAAI Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill
2022	A	`conf`	Generating and Controlling Diversity in Image Search. WACV Md. Mehrab Tanjim, Ritwik Sinha, Krishna Kumar Singh, Sridhar Mahadevan, David Arbour, Moumita Sinha, Garrison W. Cottrell
2022	J	`jnl`	Learning Relational Causal Models with Cycles through Relational Acyclification. CoRR Ragib Ahsan, David Arbour, Elena Zheleva
2022	J	`jnl`	Non-Parametric Inference of Relational Dependence. CoRR Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva
2022	A	`conf`	Non-parametric inference of relational dependence. UAI Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva
2022	J	`jnl`	Off-Policy Evaluation in Embedded Spaces. CoRR Jaron J. R. Lee, David Arbour, Georgios Theocharous
2022	A*	`conf`	Offline Evaluation of Ranked Lists using Parametric Estimation of Propensities. SIGIR Vishwa Vinay, Manoj Kilaru, David Arbour
2022	J	`jnl`	Offline Evaluation of Ranked Lists using Parametric Estimation of Propensities. CoRR Vishwa Vinay, Manoj Kilaru, David Arbour
2022	A*	`conf`	Online Balanced Experimental Design. ICML David Arbour, Drew Dimmery, Tung Mai, Anup B. Rao
2022	—	`conf`	Relational Causal Models with Cycles: Representation and Reasoning. CLeaR Ragib Ahsan, David Arbour, Elena Zheleva
2022	J	`jnl`	Relational Causal Models with Cycles: Representation and Reasoning. CoRR Ragib Ahsan, David Arbour, Elena Zheleva
2022	A*	`conf`	Sample Constrained Treatment Effect Estimation. NeurIPS Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
2022	J	`jnl`	Sample Constrained Treatment Effect Estimation. CoRR Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
2022	—	`conf`	Towards Preserving Server-Side Privacy of On-Device Models. WWW (Companion Volume) Akanksha Atrey, Ritwik Sinha, Somdeb Sarkhel, Saayan Mitra, David Arbour, Akash Maharaj, Prashant J. Shenoy
2021	C	`conf`	BOhance: Bayesian Optimization for Content Enhancement. ISM Trisha Mittal, Vishy Swaminathan, Somdeb Sarkhel, Ritwik Sinha, David Arbour, Saayan Mitra, Dinesh Manocha
2021	A*	`conf`	Causal Inference from Network Data. KDD Elena Zheleva, David Arbour
2021	J	`jnl`	Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning. CoRR Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill
2021	A	`conf`	Designing Transportable Experiments Under S-admissability. AISTATS My Phan, David Arbour, Drew Dimmery, Anup B. Rao
2021	A	`conf`	Efficient Balanced Treatment Assignments for Experimentation. AISTATS David Arbour, Drew Dimmery, Anup B. Rao
2021	J	`jnl`	Heterogeneous Graphlets. ACM Trans. Knowl. Discov. Data Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup B. Rao, Sungchul Kim, Eunyee Koh
2021	A*	`conf`	Permutation Weighting. ICML David Arbour, Drew Dimmery, Arjun Sondhi
2020	J	`jnl`	Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference. CoRR Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan A. Rossi, Tim Althoff
2020	A	`conf`	Balanced Off-Policy Evaluation in General Action Spaces. AISTATS Arjun Sondhi, David Arbour, Drew Dimmery
2020	B	`conf`	Bayesian Estimation of the Effect of Television Advertising on Web Metrics. DSAA Ritwik Sinha, Shiv Kumar Saini, Moumita Sinha, David Arbour
2020	A	`conf`	General Identification of Dynamic Treatment Regimes Under Interference. AISTATS Eli Sherman, David Arbour, Ilya Shpitser
2020	J	`jnl`	General Identification of Dynamic Treatment Regimes Under Interference. CoRR Eli Sherman, David Arbour, Ilya Shpitser
2020	J	`jnl`	Heterogeneous Graphlets. CoRR Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup B. Rao, Sungchul Kim, Eunyee Koh
2019	J	`jnl`	Balanced Off-Policy Evaluation in General Action Spaces. CoRR Arjun Sondhi, David Arbour, Drew Dimmery
2019	J	`jnl`	Heterogeneous Network Motifs. CoRR Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup Rao, Sungchul Kim, Eunyee Koh