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11/11/2021
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum
Stochastic gradient descent with momentum (SGDM) is the dominant algorit...
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06/14/2021
Robust Inference for High-Dimensional Linear Models via Residual Randomization
We propose a residual randomization procedure designed for robust Lasso-...
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05/29/2021
Randomization Inference of Periodicity in Unequally Spaced Time Series with Application to Exoplanet Detection
The estimation of periodicity is a fundamental task in many scientific a...
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06/29/2020
Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach
We propose a partial identification method for estimating disease preval...
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12/23/2019
Randomization Tests in Observational Studies with Staggered Adoption of Treatment
This paper studies inference in observational studies with time-varying ...
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10/24/2019
A Graph-Theoretic Approach to Randomization Tests of Causal Effects Under General Interference
Interference exists when a unit's outcome depends on another unit's trea...
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08/12/2019
Life After Bootstrap: Residual Randomization Inference in Regression Models
We develop a randomization-based method for inference in regression mode...
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08/09/2019
Minimax Crossover Designs
In crossover experiments, two broad types of treatment effects are typic...
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04/04/2019
Randomization tests for peer effects in group formation experiments
Measuring the effect of peers on individual outcomes is a challenging pr...
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08/27/2018
Dynamical systems theory for causal inference with application to synthetic control methods
To estimate treatment effects in panel data, suitable control units need...
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01/22/2018
Propensity score methodology in the presence of network entanglement between treatments
In experimental design and causal inference, it may happen that the trea...
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10/17/2017
Convergence diagnostics for stochastic gradient descent with constant step size
Iterative procedures in stochastic optimization are typically comprised ...
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10/04/2015
Implicit stochastic approximation
The need to carry out parameter estimation from massive data has reinvig...
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09/22/2015
Stochastic gradient descent methods for estimation with large data sets
We develop methods for parameter estimation in settings with large-scale...
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05/10/2015
Towards stability and optimality in stochastic gradient descent
Iterative procedures for parameter estimation based on stochastic gradie...
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12/21/2014
Implicit Temporal Differences
In reinforcement learning, the TD(λ) algorithm is a fundamental policy e...
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04/30/2009
