
Optimal Rates for Nonparametric Density Estimation under Communication Constraints
We consider density estimation for Besov spaces when each sample is quan...
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Principal Bit Analysis: Autoencoding with SchurConcave Loss
We consider a linear autoencoder in which the latent variables are quant...
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Robust Testing and Estimation under Manipulation Attacks
We study robust testing and estimation of discrete distributions in the ...
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Informationconstrained optimization: can adaptive processing of gradients help?
We revisit firstorder optimization under local information constraints ...
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Remember What You Want to Forget: Algorithms for Machine Unlearning
We study the problem of forgetting datapoints from a learnt model. In th...
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Inference under Information Constraints III: Local Privacy Constraints
We study goodnessoffit and independence testing of discrete distributi...
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Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints
We consider the task of estimating sparse discrete distributions under l...
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General lower bounds for interactive highdimensional estimation under information constraints
We consider the task of distributed parameter estimation using sequentia...
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Interactive Inference under Information Constraints
We consider distributed inference using sequentially interactive protoco...
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Differentially Private Assouad, Fano, and Le Cam
Le Cam's method, Fano's inequality, and Assouad's lemma are three widely...
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Estimating Entropy of Distributions in Constant Space
We consider the task of estimating the entropy of kary distributions fr...
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ContextAware Local Differential Privacy
Local differential privacy (LDP) is a strong notion of privacy for indiv...
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Optimal multiclass overfitting by sequence reconstruction from Hamming queries
A primary concern of excessive reuse of test datasets in machine learnin...
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Domain Compression and its Application to RandomnessOptimal Distributed GoodnessofFit
We study goodnessoffit of discrete distributions in the distributed se...
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Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters
We consider the problems of distribution estimation and heavy hitter (fr...
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Inference under Information Constraints II: Communication Constraints and Shared Randomness
A central server needs to perform statistical inference based on samples...
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Distributed Learning with Sublinear Communication
In distributed statistical learning, N samples are split across m machin...
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Inference under Information Constraints I: Lower Bounds from ChiSquare Contraction
We consider a distributed inference problem where only limited informati...
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Test without Trust: Optimal Locally Private Distribution Testing
We study the problem of distribution testing when the samples can only b...
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Learning and Testing Causal Models with Interventions
We consider testing and learning problems on causal Bayesian networks as...
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Distributed Simulation and Distributed Inference
Independent samples from an unknown probability distribution p on a doma...
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INSPECTRE: Privately Estimating the Unseen
We develop differentially private methods for estimating various distrib...
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Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation
We consider discrete distribution estimation over k elements under εloc...
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Measuring Quantum Entropy
The entropy of a quantum system is a measure of its randomness, and has ...
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Nearoptimalsample estimators for spherical Gaussian mixtures
Statistical and machinelearning algorithms are frequently applied to hi...
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A Fast Hierarchical Multilevel Image Segmentation Method using Unbiased Estimators
This paper proposes a novel method for segmentation of images by hierarc...
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Multilevel Thresholding for Image Segmentation through a Fast Statistical Recursive Algorithm
A novel algorithm is proposed for segmenting an image into multiple leve...
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Jayadev Acharya
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