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David T. Arbour
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2020 – today
- 2024
- [c31]Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis:
Distributional Off-Policy Evaluation for Slate Recommendations. AAAI 2024: 8265-8273 - [c30]Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra:
Editing Partially Observable Networks via Graph Diffusion Models. ICML 2024 - [c29]Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward H. Kennedy:
Continuous Treatment Effects with Surrogate Outcomes. ICML 2024 - [i18]Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward H. Kennedy:
Continuous Treatment Effects with Surrogate Outcomes. CoRR abs/2402.00168 (2024) - 2023
- [c28]Ragib Ahsan, David Arbour, Elena Zheleva:
Learning Relational Causal Models with Cycles through Relational Acyclification. AAAI 2023: 12164-12171 - [c27]Wei Zhang, David Arbour:
Online Forecasting Based Anomaly Detection For Monitoring Large Scale Streaming Data. IEEE Big Data 2023: 1998-2003 - [c26]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 - [c25]Aniket Murhekar
, David Arbour
Brief Announcement: Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. SPAA 2023: 307-310 - [c24]Akash Maharaj
Anytime-Valid Confidence Sequences in an Enterprise A/B Testing Platform. WWW (Companion Volume) 2023: 396-400 - [i17]Aniket Murhekar, David Arbour, Tung Mai, Anup Rao:
Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. CoRR abs/2304.08648 (2023) - [i16]Shreyas Chaudhari, David Arbour, Georgios Theocharous, Nikos Vlassis:
Distributional Off-Policy Evaluation for Slate Recommendations. CoRR abs/2308.14165 (2023) - [i15]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 abs/2311.17856 (2023) - 2022
- [c23]Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill:
Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning. AAAI 2022: 7841-7849 - [c22]Ragib Ahsan, David Arbour, Elena Zheleva:
Relational Causal Models with Cycles: Representation and Reasoning. CLeaR 2022: 1-18 - [c21]David Arbour, Drew Dimmery, Tung Mai, Anup B. Rao:
Online Balanced Experimental Design. ICML 2022: 844-864 - [c20]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: 1109-1120 - [c19]Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao:
Sample Constrained Treatment Effect Estimation. NeurIPS 2022 - [c18]Vishwa Vinay, Manoj Kilaru, David Arbour:
Offline Evaluation of Ranked Lists using Parametric Estimation of Propensities. SIGIR 2022: 622-632 - [c17]Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva:
Non-parametric inference of relational dependence. UAI 2022: 54-63 - [c16]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: 3908-3916 - [c15]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: 282-285 - [i14]Ragib Ahsan, David Arbour, Elena Zheleva:
Relational Causal Models with Cycles: Representation and Reasoning. CoRR abs/2202.10706 (2022) - [i13]Jaron J. R. Lee, David Arbour, Georgios Theocharous:
Off-Policy Evaluation in Embedded Spaces. CoRR abs/2203.02807 (2022) - [i12]Vishwa Vinay, Manoj Kilaru, David Arbour:
Offline Evaluation of Ranked Lists using Parametric Estimation of Propensities. CoRR abs/2206.02470 (2022) - [i11]Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva:
Non-Parametric Inference of Relational Dependence. CoRR abs/2207.00163 (2022) - [i10]Ragib Ahsan, David Arbour, Elena Zheleva:
Learning Relational Causal Models with Cycles through Relational Acyclification. CoRR abs/2208.12210 (2022) - [i9]Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao:
Sample Constrained Treatment Effect Estimation. CoRR abs/2210.06594 (2022) - 2021
- [j1]Ryan A. Rossi, Nesreen K. Ahmed
Heterogeneous Graphlets. ACM Trans. Knowl. Discov. Data 15(1): 9:1-9:43 (2021) - [c14]My Phan, David Arbour, Drew Dimmery, Anup B. Rao:
Designing Transportable Experiments Under S-admissability. AISTATS 2021: 2539-2547 - [c13]David Arbour, Drew Dimmery, Anup B. Rao:
Efficient Balanced Treatment Assignments for Experimentation. AISTATS 2021: 3070-3078 - [c12]David Arbour, Drew Dimmery, Arjun Sondhi:
Permutation Weighting. ICML 2021: 331-341 - [c11]Trisha Mittal, Vishy Swaminathan, Somdeb Sarkhel, Ritwik Sinha, David Arbour, Saayan Mitra, Dinesh Manocha:
BOhance: Bayesian Optimization for Content Enhancement. ISM 2021: 17-24 - [c10]Elena Zheleva, David Arbour:
Causal Inference from Network Data. KDD 2021: 4096-4097 - [i8]Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill:
Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning. CoRR abs/2112.15221 (2021) - 2020
- [c9]Arjun Sondhi, David Arbour, Drew Dimmery:
Balanced Off-Policy Evaluation in General Action Spaces. AISTATS 2020: 2413-2423 - [c8]Eli Sherman, David Arbour, Ilya Shpitser:
General Identification of Dynamic Treatment Regimes Under Interference. AISTATS 2020: 3917-3927 - [c7]Ritwik Sinha, Shiv Kumar Saini, Moumita Sinha, David Arbour:
Bayesian Estimation of the Effect of Television Advertising on Web Metrics. DSAA 2020: 777-778 - [i7]Eli Sherman, David Arbour, Ilya Shpitser:
General Identification of Dynamic Treatment Regimes Under Interference. CoRR abs/2004.01218 (2020) - [i6]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 abs/2009.09961 (2020) - [i5]Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup B. Rao, Sungchul Kim, Eunyee Koh:
Heterogeneous Graphlets. CoRR abs/2010.14058 (2020)
2010 – 2019
- 2019
- [i4]Ryan A. Rossi, Nesreen K. Ahmed, Aldo G. Carranza, David Arbour, Anup Rao, Sungchul Kim, Eunyee Koh:
Heterogeneous Network Motifs. CoRR abs/1901.10026 (2019) - [i3]Arjun Sondhi, David Arbour, Drew Dimmery:
Balanced Off-Policy Evaluation in General Action Spaces. CoRR abs/1906.03694 (2019) - 2016
- [c6]David T. Arbour, Dan Garant, David D. Jensen
Inferring Network Effects from Observational Data. KDD 2016: 715-724 - [c5]David T. Arbour, Katerina Marazopoulou, David D. Jensen
Inferring Causal Direction from Relational Data. UAI 2016 - 2014
- [c4]David T. Arbour, Katerina Marazopoulou, Dan Garant, David D. Jensen:
Propensity Score Matching for Causal Inference with Relational Data. CI@UAI 2014: 25-34 - [i2]Katerina Marazopoulou, David T. Arbour, David D. Jensen:
Refining the Semantics of Social Influence. CoRR abs/1412.5238 (2014) - 2013
- [c3]Marc E. Maier, Katerina Marazopoulou, David T. Arbour, David D. Jensen:
A Sound and Complete Algorithm for Learning Causal Models from Relational Data. UAI 2013 - [i1]Marc E. Maier, Katerina Marazopoulou, David T. Arbour, David D. Jensen:
A Sound and Complete Algorithm for Learning Causal Models from Relational Data. CoRR abs/1309.6843 (2013) - 2010
- [c2]Paul E. Dickson, David T. Arbour, W. Richards Adrion, Amanda Gentzel:
Evaluation of automatic classroom capture for computer science education. ITiCSE 2010: 88-92
2000 – 2009
- 2009
- [c1]Paul E. Dickson, W. Richards Adrion, Allen R. Hanson, David T. Arbour:
First experiences with a classroom recording system. ITiCSE 2009: 298-302
Coauthor Index
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last updated on 2024-09-04 01:21 CEST by the dblp team
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