10 citations · 21 across the 3 of their papers we have counts for
5 papers
Causal Matrix Completion
Anish Agarwal, Munther Dahleh, Devavrat Shah +1
Matrix completion is the study of recovering an underlying matrix from a sparse subset of noisy observations. Traditionally, it is assumed that the entries of the matrix are "missi…
Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?
Anish Agarwal, Abdullah Alomar, Arnab Sarker +3
As we reach the apex of the COVID-19 pandemic, the most pressing question facing us is: can we even partially reopen the economy without risking a second wave? We first need to und…
mRSC: Multi-dimensional Robust Synthetic Control
Muhummad Amjad, Vishal Misra, Devavrat Shah +1
When evaluating the impact of a policy on a metric of interest, it may not be possible to conduct a randomized control trial. In settings where only observational data is available…
Model Agnostic Time Series Analysis via Matrix Estimation
Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah +1
We propose an algorithm to impute and forecast a time series by transforming the observed time series into a matrix, utilizing matrix estimation to recover missing values and de-no…
Robust Synthetic Control
Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen
We present a robust generalization of the synthetic control method for comparative case studies. Like the classical method, we present an algorithm to estimate the unobservable cou…