David Arbour

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 41

Top Topics

Diffusion Model

Policy Evaluation

Top Venues

Publications

Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward H. Kennedy
Continuous Treatment Effects with Surrogate Outcomes. CoRR (2024)
Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis
Distributional Off-Policy Evaluation for Slate Recommendations. AAAI (2024)
Aniket Murhekar, David Arbour, Tung Mai, Anup Rao
Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. CoRR (2023)
Aniket Murhekar, David Arbour, Tung Mai, Anup B. Rao
Brief Announcement: Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. SPAA (2023)
Wei Zhang, David Arbour
Online Forecasting Based Anomaly Detection For Monitoring Large Scale Streaming Data. BigData (2023)
Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis
Distributional Off-Policy Evaluation for Slate Recommendations. CoRR (2023)
Ragib Ahsan, David Arbour, Elena Zheleva
Learning Relational Causal Models with Cycles through Relational Acyclification. AAAI (2023)
Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. NeurIPS (2023)
Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
Leveraging Graph Diffusion Models for Network Refinement Tasks. CoRR (2023)
Akash Maharaj, Ritwik Sinha, David Arbour, Ian Waudby-Smith, Simon Z. Liu, Moumita Sinha, Raghavendra Addanki, Aaditya Ramdas, Manas Garg, Viswanathan Swaminathan
Anytime-Valid Confidence Sequences in an Enterprise A/B Testing Platform. WWW (Companion Volume) (2023)
Vishwa Vinay, Manoj Kilaru, David Arbour
Offline Evaluation of Ranked Lists using Parametric Estimation of Propensities. CoRR (2022)
Jaron J. R. Lee, David Arbour, Georgios Theocharous
Off-Policy Evaluation in Embedded Spaces. CoRR (2022)
Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva
Non-parametric inference of relational dependence. UAI (2022)
Ragib Ahsan, David Arbour, Elena Zheleva
Relational Causal Models with Cycles: Representation and Reasoning. CoRR (2022)
Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
Sample Constrained Treatment Effect Estimation. CoRR (2022)
Vishwa Vinay, Manoj Kilaru, David Arbour
Offline Evaluation of Ranked Lists using Parametric Estimation of Propensities. SIGIR (2022)
Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
Sample Constrained Treatment Effect Estimation. NeurIPS (2022)
Ragib Ahsan, David Arbour, Elena Zheleva
Learning Relational Causal Models with Cycles through Relational Acyclification. CoRR (2022)
Md. Mehrab Tanjim, Ritwik Sinha, Krishna Kumar Singh, Sridhar Mahadevan, David Arbour, Moumita Sinha, Garrison W. Cottrell
Generating and Controlling Diversity in Image Search. WACV (2022)
Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan A. Rossi, Tim Althoff
Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference. ICWSM (2022)
Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill
Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning. AAAI (2022)
Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva
Non-Parametric Inference of Relational Dependence. CoRR (2022)
Akanksha Atrey, Ritwik Sinha, Somdeb Sarkhel, Saayan Mitra, David Arbour, Akash Maharaj, Prashant J. Shenoy
Towards Preserving Server-Side Privacy of On-Device Models. WWW (Companion Volume) (2022)
Ragib Ahsan, David Arbour, Elena Zheleva
Relational Causal Models with Cycles: Representation and Reasoning. CLeaR (2022)
David Arbour, Drew Dimmery, Tung Mai, Anup B. Rao
Online Balanced Experimental Design. ICML (2022)
David Arbour, Drew Dimmery, Arjun Sondhi
Permutation Weighting. ICML (2021)
Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup B. Rao, Sungchul Kim, Eunyee Koh
Heterogeneous Graphlets. ACM Trans. Knowl. Discov. Data 15 (1) (2021)
David Arbour, Drew Dimmery, Anup B. Rao
Efficient Balanced Treatment Assignments for Experimentation. AISTATS (2021)
Trisha Mittal, Vishy Swaminathan, Somdeb Sarkhel, Ritwik Sinha, David Arbour, Saayan Mitra, Dinesh Manocha
BOhance: Bayesian Optimization for Content Enhancement. ISM (2021)
Elena Zheleva, David Arbour
Causal Inference from Network Data. KDD (2021)
Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill
Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning. CoRR (2021)
My Phan, David Arbour, Drew Dimmery, Anup B. Rao
Designing Transportable Experiments Under S-admissability. AISTATS (2021)
David Arbour, Drew Dimmery, Tung Mai, Anup B. Rao
Online Discrepancy Minimization via Persistent Self-Balancing Walks. CoRR (2021)
Eli Sherman, David Arbour, Ilya Shpitser
General Identification of Dynamic Treatment Regimes Under Interference. CoRR (2020)
Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan A. Rossi, Tim Althoff
Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference. CoRR (2020)
Ritwik Sinha, Shiv Kumar Saini, Moumita Sinha, David Arbour
Bayesian Estimation of the Effect of Television Advertising on Web Metrics. DSAA (2020)
Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup B. Rao, Sungchul Kim, Eunyee Koh
Heterogeneous Graphlets. CoRR (2020)
Arjun Sondhi, David Arbour, Drew Dimmery
Balanced Off-Policy Evaluation in General Action Spaces. AISTATS (2020)
Eli Sherman, David Arbour, Ilya Shpitser
General Identification of Dynamic Treatment Regimes Under Interference. AISTATS (2020)
Arjun Sondhi, David Arbour, Drew Dimmery
Balanced Off-Policy Evaluation in General Action Spaces. CoRR (2019)
Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup Rao, Sungchul Kim, Eunyee Koh
Heterogeneous Network Motifs. CoRR (2019)