Anish Agarwal | DeepAI

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∙ 07/03/2023

Adaptive Principal Component Regression with Applications to Panel Data

Principal component regression (PCR) is a popular technique for fixed-de...

0 Anish Agarwal, et al. ∙

∙ 06/21/2023

Estimating the Value of Evidence-Based Decision Making

Business/policy decisions are often based on evidence from randomized ex...

0 Alberto Abadie, et al. ∙

∙ 03/24/2023

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions

We consider a setting with N heterogeneous units and p interventions. Ou...

0 Abhineet Agarwal, et al. ∙

∙ 11/25/2022

Strategyproof Decision-Making in Panel Data Settings and Beyond

We propose a framework for decision-making in the presence of strategic ...

0 Keegan Harris, et al. ∙

∙ 10/20/2022

Network Synthetic Interventions: A Framework for Panel Data with Network Interference

We propose a generalization of the synthetic controls and synthetic inte...

0 Anish Agarwal, et al. ∙

∙ 10/20/2022

Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime

We propose a generalization of the synthetic control and synthetic inter...

0 Anish Agarwal, et al. ∙

∙ 01/05/2022

CausalSim: Unbiased Trace-Driven Network Simulation

Evaluating the real-world performance of network protocols is challengin...

3 Abdullah Alomar, et al. ∙

∙ 09/30/2021

Causal Matrix Completion

Matrix completion is the study of recovering an underlying matrix from a...

10 Anish Agarwal, et al. ∙

∙ 07/06/2021

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

Even the most carefully curated economic data sets have variables that a...

0 Anish Agarwal, et al. ∙

∙ 02/13/2021

PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators

We consider offline reinforcement learning (RL) with heterogeneous agent...

12 Anish Agarwal, et al. ∙

∙ 11/05/2020

Causal Imputation via Synthetic Interventions

Consider the problem of determining the effect of a drug on a specific c...

0 Chandler Squires, et al. ∙

∙ 10/27/2020

On Principal Component Regression in a High-Dimensional Error-in-Variables Setting

We analyze the classical method of Principal Component Regression (PCR) ...

4 Anish Agarwal, et al. ∙

∙ 06/24/2020

On Multivariate Singular Spectrum Analysis

We analyze a variant of multivariate singular spectrum analysis (mSSA), ...

3 Anish Agarwal, et al. ∙

∙ 06/13/2020

Synthetic Interventions

We develop a method to help quantify the impact different levels of mobi...

5 Anish Agarwal, et al. ∙

∙ 04/30/2020

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

As we reach the apex of the COVID-19 pandemic, the most pressing questio...

0 Anish Agarwal, et al. ∙

∙ 03/31/2020

Augmented Q Imitation Learning (AQIL)

The study of unsupervised learning can be generally divided into two cat...

0 Xiao-Lei Zhang, et al. ∙

∙ 03/18/2020

Towards Data Auctions with Externalities

The design of data markets has gained in importance as firms increasingl...

0 Anish Agarwal, et al. ∙

∙ 02/28/2019

Model Agnostic High-Dimensional Error-in-Variable Regression

We consider the problem of high-dimensional error-in-variable regression...

0 Anish Agarwal, et al. ∙

∙ 05/21/2018

A Marketplace for Data: An Algorithmic Solution

In this work, we aim to create a data marketplace; a robust real-time ma...

0 Anish Agarwal, et al. ∙

∙ 02/25/2018

Time Series Analysis via Matrix Estimation

We consider the task of interpolating and forecasting a time series in t...

0 Anish Agarwal, et al. ∙

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