Moulinath Banerjee | DeepAI

AI Chat

Featured Co-authors

Rui Song
75 publications
George Michailidis
47 publications
Mikhail Yurochkin
43 publications
Yuekai Sun
38 publications
Michael R. Kosorok
36 publications
Ya'acov Ritov
22 publications
Eric B. Laber
18 publications
Debarghya Mukherjee
13 publications
Subha Maity
11 publications
Felipe Maia Polo
7 publications
Rohit K. Patra
5 publications

∙ 07/05/2023

Conditional independence testing under model misspecification

Conditional independence (CI) testing is fundamental and challenging in ...

0 Felipe Maia Polo, et al. ∙

∙ 06/13/2022

Inference for change-plane regression

We establish the asymptotic behavior of change-plane estimators. Two typ...

0 Chaeryon Kang, et al. ∙

∙ 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...

0 Subha Maity, et al. ∙

∙ 05/26/2022

Predictor-corrector algorithms for stochastic optimization under gradual distribution shift

Time-varying stochastic optimization problems frequently arise in machin...

0 Subha Maity, et al. ∙

∙ 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...

0 Subha Maity, et al. ∙

∙ 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 ...

0 Debarghya Mukherjee, et al. ∙

∙ 02/22/2021

Regression discontinuity design: estimating the treatment effect with standard parametric rate

Regression discontinuity design models are widely used for the assessmen...

0 Debarghya Mukherjee, et al. ∙

∙ 12/03/2020

A semi-parametric model for target localization in distributed systems

Distributed systems serve as a key technological infrastructure for moni...

0 Rohit K. Patra, et al. ∙

∙ 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...

0 Hamid Eftekhari, et al. ∙

∙ 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...

0 Hamid Eftekhari, et al. ∙

∙ 06/19/2020

Two Simple Ways to Learn Individual Fairness Metrics from Data

Individual fairness is an intuitive definition of algorithmic fairness t...

0 Debarghya Mukherjee, et al. ∙

∙ 03/23/2020

Minimax optimal approaches to the label shift problem

We study minimax rates of convergence in the label shift problem. In add...

0 Subha Maity, et al. ∙

∙ 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...

0 Debarghya Mukherjee, et al. ∙

∙ 12/26/2019

Communication-Efficient Integrative Regression in High-Dimensions

We consider the task of meta-analysis in high-dimensional settings in wh...

0 Subha Maity, et al. ∙

∙ 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 ...

0 Hamid Eftekhari, et al. ∙

∙ 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...

0 Monika Bhattacharjee, et al. ∙

∙ 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 ...

0 Debarghya Mukherjee, et al. ∙

∙ 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...

0 Monika Bhattacharjee, et al. ∙

∙ 06/22/2018

Removing the Curse of Superefficiency: an Effective Strategy For Distributed Computing in Isotonic Regression

We propose a strategy for computing the isotonic least-squares estimate ...

0 Moulinath Banerjee, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world