Anish Agarwal

According to our database1, Anish Agarwal authored at least 33 papers between 2015 and 2024.

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Bibliography

2024
Doubly Robust Inference in Causal Latent Factor Models.
CoRR, 2024

2023
Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration.
CoRR, 2023

Adaptive Principal Component Regression with Applications to Panel Data.
CoRR, 2023

Estimating the Value of Evidence-Based Decision Making.
CoRR, 2023

CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation.
Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation, 2023

Adaptive Principal Component Regression with Applications to Panel Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Matrix Completion.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Causal Inference for Social and Engineering Systems.
SIGMETRICS Perform. Evaluation Rev., December, 2022

Strategyproof Decision-Making in Panel Data Settings and Beyond.
CoRR, 2022

Network Synthetic Interventions: A Framework for Panel Data with Network Interference.
CoRR, 2022

Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime.
CoRR, 2022

CausalSim: Toward a Causal Data-Driven Simulator for Network Protocols.
CoRR, 2022

On Multivariate Singular Spectrum Analysis and Its Variants.
Proceedings of the SIGMETRICS/PERFORMANCE '22: ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, Mumbai, India, June 6, 2022

Causal Imputation via Synthetic Interventions.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy.
CoRR, 2021

PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
On the Inefficiency of Forward Markets in Leader-Follower Competition.
Oper. Res., 2020

On Principal Component Regression in a High-Dimensional Error-in-Variables Setting.
CoRR, 2020

On Multivariate Singular Spectrum Analysis.
CoRR, 2020

Synthetic Interventions.
CoRR, 2020

Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?
CoRR, 2020

Augmented Q Imitation Learning (AQIL).
CoRR, 2020

Towards Data Auctions with Externalities.
CoRR, 2020

tspDB: Time Series Predict DB.
Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Single Image Super-Resolution using Residual Channel Attention Network.
Proceedings of the 15th IEEE International Conference on Industrial and Information Systems, 2020

2019
Zorro: A Model Agnostic System to Price Consumer Data.
CoRR, 2019

Model Agnostic High-Dimensional Error-in-Variable Regression.
CoRR, 2019

On Robustness of Principal Component Regression.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Marketplace for Data: An Algorithmic Solution.
Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

2018
Model Agnostic Time Series Analysis via Matrix Estimation.
Proc. ACM Meas. Anal. Comput. Syst., 2018

Time Series Analysis via Matrix Estimation.
CoRR, 2018

2015
Online Convex Optimization Using Predictions.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015


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