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2020 – today
- 2024
[c14]Keegan Harris
, Anish Agarwal, Chara Podimata, Zhiwei Steven Wu:
Strategyproof Decision-Making in Panel Data Settings and Beyond. SIGMETRICS/Performance (Abstracts) 2024: 69-70- [i24]Alberto Abadie, Anish Agarwal, Raaz Dwivedi, Abhin Shah:
Doubly Robust Inference in Causal Latent Factor Models. CoRR abs/2402.11652 (2024) - [i23]Abhineet Agarwal, Anish Agarwal, Lorenzo Masoero, Justin Whitehouse:
Multi-Armed Bandits with Network Interference. CoRR abs/2405.18621 (2024) - 2023
- [c13]Anish Agarwal, Munther A. Dahleh, Devavrat Shah, Dennis Shen:
Causal Matrix Completion. COLT 2023: 3821-3826 - [c12]Abhineet Agarwal, Anish Agarwal, Suhas Vijaykumar:
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions. NeurIPS 2023 - [c11]Anish Agarwal, Keegan Harris, Justin Whitehouse, Zhiwei Steven Wu:
Adaptive Principal Component Regression with Applications to Panel Data. NeurIPS 2023 - [c10]Abdullah Alomar, Pouya Hamadanian, Arash Nasr-Esfahany, Anish Agarwal, Mohammad Alizadeh, Devavrat Shah:
CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation. NSDI 2023: 1115-1147 - [i22]Abhineet Agarwal, Anish Agarwal, Suhas Vijaykumar:
Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions. CoRR abs/2303.14226 (2023) - [i21]Alberto Abadie, Anish Agarwal, Guido Imbens, Siwei Jia, James McQueen, Serguei Stepaniants:
Estimating the Value of Evidence-Based Decision Making. CoRR abs/2306.13681 (2023) - [i20]Anish Agarwal, Keegan Harris, Justin Whitehouse, Zhiwei Steven Wu:
Adaptive Principal Component Regression with Applications to Panel Data. CoRR abs/2307.01357 (2023) - [i19]Dung Daniel T. Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis, Zhiwei Steven Wu:
Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration. CoRR abs/2312.16307 (2023) - 2022
- [b1]Anish Agarwal:
Causal Inference for Social and Engineering Systems. MIT, USA, 2022 - [j3]Anish Agarwal:
Causal Inference for Social and Engineering Systems. SIGMETRICS Perform. Evaluation Rev. 50(3): 7-11 (2022) - [c9]Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler:
Causal Imputation via Synthetic Interventions. CLeaR 2022: 688-711 - [c8]Anish Agarwal, Abdullah Alomar, Devavrat Shah:
On Multivariate Singular Spectrum Analysis and Its Variants. SIGMETRICS (Abstracts) 2022: 79-80 - [i18]Abdullah Alomar, Pouya Hamadanian, Arash Nasr-Esfahany, Anish Agarwal, Mohammad Alizadeh, Devavrat Shah:
CausalSim: Toward a Causal Data-Driven Simulator for Network Protocols. CoRR abs/2201.01811 (2022) - [i17]Anish Agarwal, Vasilis Syrgkanis:
Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime. CoRR abs/2210.11003 (2022) - [i16]Anish Agarwal, Sarah H. Cen, Devavrat Shah, Christina Lee Yu:
Network Synthetic Interventions: A Framework for Panel Data with Network Interference. CoRR abs/2210.11355 (2022) - [i15]Keegan Harris, Anish Agarwal, Chara Podimata, Zhiwei Steven Wu:
Strategyproof Decision-Making in Panel Data Settings and Beyond. CoRR abs/2211.14236 (2022) - 2021
- [c7]Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang:
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators. NeurIPS 2021: 18564-18576 - [i14]Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang:
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators. CoRR abs/2102.06961 (2021) - [i13]Anish Agarwal, Rahul Singh:
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy. CoRR abs/2107.02780 (2021) - [i12]Anish Agarwal, Munther A. Dahleh, Devavrat Shah, Dennis Shen:
Causal Matrix Completion. CoRR abs/2109.15154 (2021) - 2020
- [j2]Desmond W. H. Cai, Anish Agarwal, Adam Wierman:
On the Inefficiency of Forward Markets in Leader-Follower Competition. Oper. Res. 68(1): 35-52 (2020) - [c6]Hritam Basak, Rohit Kundu, Anish Agarwal, Shreya Giri:
Single Image Super-Resolution using Residual Channel Attention Network. ICIIS 2020: 219-224 - [c5]Anish Agarwal, Abdullah Alomar, Devavrat Shah:
tspDB: Time Series Predict DB. NeurIPS (Competition and Demos) 2020: 27-56 - [i11]Anish Agarwal, Munther A. Dahleh, Thibaut Horel, Maryann Rui:
Towards Data Auctions with Externalities. CoRR abs/2003.08345 (2020) - [i10]Xiao-Lei Zhang, Anish Agarwal:
Augmented Q Imitation Learning (AQIL). CoRR abs/2004.00993 (2020) - [i9]Anish Agarwal, Abdullah Alomar, Arnab Sarker, Devavrat Shah, Dennis Shen, Cindy Yang:
Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave? CoRR abs/2005.00072 (2020) - [i8]Anish Agarwal, Abdullah Alomar, Romain Cosson, Devavrat Shah, Dennis Shen:
Synthetic Interventions. CoRR abs/2006.07691 (2020) - [i7]Anish Agarwal, Abdullah Alomar, Devavrat Shah:
On Multivariate Singular Spectrum Analysis. CoRR abs/2006.13448 (2020) - [i6]Anish Agarwal, Devavrat Shah, Dennis Shen:
On Principal Component Regression in a High-Dimensional Error-in-Variables Setting. CoRR abs/2010.14449 (2020)
2010 – 2019
- 2019
- [c4]Anish Agarwal, Munther A. Dahleh, Tuhin Sarkar:
A Marketplace for Data: An Algorithmic Solution. EC 2019: 701-726 - [c3]Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song:
On Robustness of Principal Component Regression. NeurIPS 2019: 9889-9900 - [c2]Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen:
Model Agnostic Time Series Analysis via Matrix Estimation. SIGMETRICS (Abstracts) 2019: 85-86 - [i5]Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song:
Model Agnostic High-Dimensional Error-in-Variable Regression. CoRR abs/1902.10920 (2019) - [i4]Anish Agarwal, Munther A. Dahleh, Devavrat Shah, Dylan Sleeper, Andrew Tsai, Madeline Wong:
Zorro: A Model Agnostic System to Price Consumer Data. CoRR abs/1906.02420 (2019) - 2018
- [j1]Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen:
Model Agnostic Time Series Analysis via Matrix Estimation. Proc. ACM Meas. Anal. Comput. Syst. 2(3): 40:1-40:39 (2018) - [i3]Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen:
Time Series Analysis via Matrix Estimation. CoRR abs/1802.09064 (2018) - [i2]Anish Agarwal, Munther A. Dahleh, Tuhin Sarkar:
A Marketplace for Data: An Algorithmic Solution. CoRR abs/1805.08125 (2018) - 2015
- [c1]Niangjun Chen, Anish Agarwal, Adam Wierman, Siddharth Barman, Lachlan L. H. Andrew:
Online Convex Optimization Using Predictions. SIGMETRICS 2015: 191-204 - [i1]Niangjun Chen, Anish Agarwal, Adam Wierman, Siddharth Barman, Lachlan L. H. Andrew:
Online Convex Optimization Using Predictions. CoRR abs/1504.06681 (2015)
Coauthor Index
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last updated on 2024-08-29 21:51 CEST by the dblp team
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