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12/21/2022
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
We introduce camouflaged data poisoning attacks, a new attack vector tha...
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11/07/2022
Discrete Distribution Estimation under User-level Local Differential Privacy
We study discrete distribution estimation under user-level local differe...
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03/14/2022
The Role of Interactivity in Structured Estimation
We study high-dimensional sparse estimation under three natural constrai...
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07/21/2021
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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06/05/2021
Principal Bit Analysis: Autoencoding with Schur-Concave Loss
We consider a linear autoencoder in which the latent variables are quant...
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04/21/2021
Robust Testing and Estimation under Manipulation Attacks
We study robust testing and estimation of discrete distributions in the ...
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04/02/2021
Information-constrained optimization: can adaptive processing of gradients help?
We revisit first-order optimization under local information constraints ...
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03/04/2021
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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01/20/2021
Inference under Information Constraints III: Local Privacy Constraints
We study goodness-of-fit and independence testing of discrete distributi...
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10/30/2020
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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10/13/2020
General lower bounds for interactive high-dimensional estimation under information constraints
We consider the task of distributed parameter estimation using sequentia...
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07/21/2020
Interactive Inference under Information Constraints
We consider distributed inference using sequentially interactive protoco...
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04/14/2020
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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11/18/2019
Estimating Entropy of Distributions in Constant Space
We consider the task of estimating the entropy of k-ary distributions fr...
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10/31/2019
Context-Aware Local Differential Privacy
Local differential privacy (LDP) is a strong notion of privacy for indiv...
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08/08/2019
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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07/20/2019
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit
We study goodness-of-fit of discrete distributions in the distributed se...
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05/28/2019
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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05/20/2019
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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02/28/2019
Distributed Learning with Sublinear Communication
In distributed statistical learning, N samples are split across m machin...
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12/30/2018
Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction
We consider a distributed inference problem where only limited informati...
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08/07/2018
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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05/24/2018
Learning and Testing Causal Models with Interventions
We consider testing and learning problems on causal Bayesian networks as...
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04/19/2018
Distributed Simulation and Distributed Inference
Independent samples from an unknown probability distribution p on a doma...
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02/28/2018
INSPECTRE: Privately Estimating the Unseen
We develop differentially private methods for estimating various distrib...
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02/13/2018
Communication Efficient, Sample Optimal, Linear Time Locally Private Discrete Distribution Estimation
We consider discrete distribution estimation over k elements under ε-loc...
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11/02/2017
Measuring Quantum Entropy
The entropy of a quantum system is a measure of its randomness, and has ...
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02/19/2014
Near-optimal-sample estimators for spherical Gaussian mixtures
Statistical and machine-learning algorithms are frequently applied to hi...
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12/24/2007
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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02/12/2006