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07/05/2023
Conditional independence testing under model misspecification
Conditional independence (CI) testing is fundamental and challenging in ...
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06/13/2022
Inference for change-plane regression
We establish the asymptotic behavior of change-plane estimators. Two typ...
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05/26/2022
Understanding new tasks through the lens of training data via exponential tilting
Deploying machine learning models to new tasks is a major challenge desp...
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05/26/2022
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift
Time-varying stochastic optimization problems frequently arise in machin...
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11/21/2021
A linear adjustment based approach to posterior drift in transfer learning
We present a new model and methods for the posterior drift problem where...
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05/25/2021
On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions
This paper presents a number of new findings about the canonical change ...
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02/22/2021
Regression discontinuity design: estimating the treatment effect with standard parametric rate
Regression discontinuity design models are widely used for the assessmen...
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12/03/2020
A semi-parametric model for target localization in distributed systems
Distributed systems serve as a key technological infrastructure for moni...
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10/23/2020
Design of c-Optimal Experiments for High dimensional Linear Models
We study random designs that minimize the asymptotic variance of a de-bi...
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08/02/2020
Markovian And Non-Markovian Processes with Active Decision Making Strategies For Addressing The COVID-19 Pandemic
We study and predict the evolution of Covid-19 in six US states from the...
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06/19/2020
Two Simple Ways to Learn Individual Fairness Metrics from Data
Individual fairness is an intuitive definition of algorithmic fairness t...
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03/23/2020
Minimax optimal approaches to the label shift problem
We study minimax rates of convergence in the label shift problem. In add...
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01/20/2020
Asymptotic normality of a linear threshold estimator in fixed dimension with near-optimal rate
Linear thresholding models postulate that the conditional distribution o...
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12/26/2019
Communication-Efficient Integrative Regression in High-Dimensions
We consider the task of meta-analysis in high-dimensional settings in wh...
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09/08/2019
Inference In General Single-Index Models Under High-dimensional Symmetric Designs
We consider the problem of statistical inference for a finite number of ...
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04/25/2019
Change Point Estimation in Panel Data with Temporal and Cross-sectional Dependence
We study the problem of detecting a common change point in large panel d...
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03/24/2019
Non-Standard Asymptotics in High Dimensions: Manski's Maximum Score Estimator Revisited
Manski's celebrated maximum score estimator for the binary choice model ...
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12/07/2018
Change Point Estimation in a Dynamic Stochastic Block Model
We consider the problem of estimating the location of a single change po...
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06/22/2018