Anindya De | DeepAI

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293 publications
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Rocco A. Servedio
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Philip M. Long
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Aravindan Vijayaraghavan
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Ryan O'Donnell
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Sanjeev Khanna
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Emmanouil-Vasileios Vlatakis-Gkaragkounis
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Sampath Kannan
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∙ 05/04/2023

Testing Convex Truncation

We study the basic statistical problem of testing whether normally distr...

0 Anindya De, et al. ∙

∙ 11/07/2022

Approximate Trace Reconstruction from a Single Trace

The well-known trace reconstruction problem is the problem of inferring ...

0 Xi Chen, et al. ∙

∙ 06/15/2022

Reconstructing Ultrametric Trees from Noisy Experiments

The problem of reconstructing evolutionary trees or phylogenies is of gr...

0 Eshwar Ram Arunachaleswaran, et al. ∙

∙ 09/07/2021

Convex Influences

We introduce a new notion of influence for symmetric convex sets over Ga...

0 Anindya De, et al. ∙

∙ 07/26/2021

Approximating Sumset Size

Given a subset A of the n-dimensional Boolean hypercube 𝔽_2^n, the sumse...

0 Anindya De, et al. ∙

∙ 07/24/2021

Near-Optimal Average-Case Approximate Trace Reconstruction from Few Traces

In the standard trace reconstruction problem, the goal is to exactly rec...

0 Xi Chen, et al. ∙

∙ 12/22/2020

Quantitative Correlation Inequalities via Semigroup Interpolation

Most correlation inequalities for high-dimensional functions in the lite...

0 Anindya De, et al. ∙

∙ 12/04/2020

Polynomial-time trace reconstruction in the low deletion rate regime

In the trace reconstruction problem, an unknown source string x ∈{0,1}^n...

0 Xi Chen, et al. ∙

∙ 10/06/2020

Learning a mixture of two subspaces over finite fields

We study the problem of learning a mixture of two subspaces over 𝔽_2^n. ...

0 Aidao Chen, et al. ∙

∙ 08/27/2020

Polynomial-time trace reconstruction in the smoothed complexity model

In the trace reconstruction problem, an unknown source string x ∈{0,1}^n...

0 Xi Chen, et al. ∙

∙ 07/19/2020

Reconstructing weighted voting schemes from partial information about their power indices

A number of recent works [Goldberg 2006; O'Donnell and Servedio 2011; De...

0 Huck Bennett, et al. ∙

∙ 06/23/2020

An Efficient PTAS for Stochastic Load Balancing with Poisson Jobs

We give the first polynomial-time approximation scheme (PTAS) for the st...

0 Anindya De, et al. ∙

∙ 04/24/2020

Robust testing of low-dimensional functions

A natural problem in high-dimensional inference is to decide if a classi...

0 Anindya De, et al. ∙

∙ 11/03/2019

Testing noisy linear functions for sparsity

We consider the following basic inference problem: there is an unknown h...

0 Xue Chen, et al. ∙

∙ 11/01/2019

Kruskal-Katona for convex sets, with applications

The well-known Kruskal-Katona theorem in combinatorics says that (under ...

0 Anindya De, et al. ∙

∙ 07/09/2019

Reconstruction under outliers for Fourier-sparse functions

We consider the problem of learning an unknown f with a sparse Fourier s...

0 Xue Chen, et al. ∙

∙ 07/02/2019

Learning from satisfying assignments under continuous distributions

What kinds of functions are learnable from their satisfying assignments?...

0 Clément L. Canonne, et al. ∙

∙ 04/08/2019

Junta correlation is testable

The problem of tolerant junta testing is a natural and challenging probl...

0 Anindya De, et al. ∙

∙ 11/09/2018

Density estimation for shift-invariant multidimensional distributions

We study density estimation for classes of shift-invariant distributions...

0 Anindya De, et al. ∙

∙ 11/03/2018

Learning sparse mixtures of rankings from noisy information

We study the problem of learning an unknown mixture of k rankings over n...

0 Anindya De, et al. ∙

∙ 07/18/2018

Learning Sums of Independent Random Variables with Sparse Collective Support

We study the learnability of sums of independent integer random variable...

0 Anindya De, et al. ∙

∙ 06/26/2018

Is your function low-dimensional?

We study the problem of testing if a function depends on a small number ...

0 Anindya De, et al. ∙

∙ 06/26/2018

Is your data low-dimensional?

We study the problem of testing if a function depends on a small number ...

0 Anindya De, et al. ∙

∙ 12/04/2017

Boolean function analysis meets stochastic optimization: An approximation scheme for stochastic knapsack

The stochastic knapsack problem is the stochastic variant of the classic...

0 Anindya De, et al. ∙

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