Search Results for author: Dennis Shen

Found 10 papers, 7 papers with code

Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator

1 code implementation27 Sep 2023 Dennis Shen, Dogyoon Song, Peng Ding, Jasjeet S. Sekhon

Deep learning research has uncovered the phenomenon of benign overfitting for overparameterized statistical models, which has drawn significant theoretical interest in recent years.

Causal Inference

Causal Matrix Completion

1 code implementation30 Sep 2021 Anish Agarwal, Munther Dahleh, Devavrat Shah, Dennis Shen

In particular, we establish entry-wise, i. e., max-norm, finite-sample consistency and asymptotic normality results for matrix completion with MNAR data.

Matrix Completion Recommendation Systems

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

no code implementations NeurIPS 2021 Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang

We consider offline reinforcement learning (RL) with heterogeneous agents under severe data scarcity, i. e., we only observe a single historical trajectory for every agent under an unknown, potentially sub-optimal policy.

Offline RL reinforcement-learning +1

On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls

1 code implementation27 Oct 2020 Anish Agarwal, Devavrat Shah, Dennis Shen

To the best of our knowledge, our prediction guarantees for the fixed design setting have been elusive in both the high-dimensional error-in-variables and synthetic controls literatures.

Synthetic Interventions

1 code implementation13 Jun 2020 Anish Agarwal, Devavrat Shah, Dennis Shen

Towards this, we present a causal framework, synthetic interventions (SI), to infer these $N \times D$ causal parameters while only observing each of the $N$ units under at most two interventions, independent of $D$.

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

no code implementations30 Apr 2020 Anish Agarwal, Abdullah Alomar, Arnab Sarker, Devavrat Shah, Dennis Shen, Cindy Yang

In essence, the method leverages information from different interventions that have already been enacted across the world and fits it to a policy maker's setting of interest, e. g., to estimate the effect of mobility-restricting interventions on the U. S., we use daily death data from countries that enforced severe mobility restrictions to create a "synthetic low mobility U. S." and predict the counterfactual trajectory of the U. S. if it had indeed applied a similar intervention.


On Robustness of Principal Component Regression

no code implementations NeurIPS 2019 Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song

As an important contribution to the Synthetic Control literature, we establish that an (approximate) linear synthetic control exists in the setting of a generalized factor model; traditionally, the existence of a synthetic control needs to be assumed to exist as an axiom.

Art Analysis Causal Inference +3

Model Agnostic Time Series Analysis via Matrix Estimation

1 code implementation25 Feb 2018 Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen

In effect, this generalizes the widely used Singular Spectrum Analysis (SSA) in time series literature, and allows us to establish a rigorous link between time series analysis and matrix estimation.

Imputation regression +2

Robust Synthetic Control

1 code implementation18 Nov 2017 Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen

Our experiments, using both real-world and synthetic datasets, demonstrate that our robust generalization yields an improvement over the classical synthetic control method.


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