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04/22/2022
Bridging Sapling: Private Cross-Chain Transfers
Interoperability is one of the main challenges of blockchain technologie...
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06/17/2021
Statistical Query Lower Bounds for List-Decodable Linear Regression
We study the problem of list-decodable linear regression, where an adver...
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02/03/2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition
We study the problem of learning Ising models satisfying Dobrushin's con...
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07/03/2020
GRANDPA: a Byzantine Finality Gadget
Classic Byzantine fault-tolerant consensus protocols forfeit liveness in...
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05/27/2020
Overview of Polkadot and its Design Considerations
In this paper we describe the design components of the heterogenous mult...
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04/27/2020
Validator election in nominated proof-of-stake
Polkadot is a decentralized blockchain platform to be launched in 2020. ...
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11/19/2019
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
We study high-dimensional sparse estimation tasks in a robust setting wh...
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07/18/2019
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
We consider the problem of computing the maximum likelihood multivariate...
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12/13/2018
A Polynomial Time Algorithm for Maximum Likelihood Estimation of Multivariate Log-concave Densities
We study the problem of computing the maximum likelihood estimator (MLE)...
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06/11/2018
Reachability for Branching Concurrent Stochastic Games
We give polynomial time algorithms for deciding almost-sure and limit-su...
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05/31/2018
Efficient Algorithms and Lower Bounds for Robust Linear Regression
We study the problem of high-dimensional linear regression in a robust m...
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03/07/2018
Sever: A Robust Meta-Algorithm for Stochastic Optimization
In high dimensions, most machine learning methods are brittle to even a ...
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02/28/2018
Near-Optimal Sample Complexity Bounds for Maximum Likelihood Estimation of Multivariate Log-concave Densities
We study the problem of learning multivariate log-concave densities with...
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11/30/2017
Testing Conditional Independence of Discrete Distributions
We study the problem of testing conditional independence for discrete di...
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11/20/2017
List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians
We study the problem of list-decodable Gaussian mean estimation and the ...
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07/05/2017
Learning Geometric Concepts with Nasty Noise
We study the efficient learnability of geometric concept classes - speci...
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04/12/2017
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently
We study the fundamental problem of learning the parameters of a high-di...
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03/02/2017
Being Robust (in High Dimensions) Can Be Practical
Robust estimation is much more challenging in high dimensions than it is...
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06/23/2016
Robust Learning of Fixed-Structure Bayesian Networks
We investigate the problem of learning Bayesian networks in an agnostic ...
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04/21/2016