
ListDecodable Coded Computing: Breaking the Adversarial Toleration Barrier
We consider the problem of coded computing where a computational task is...
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On Polynomial Approximations for PrivacyPreserving and Verifiable ReLU Networks
Outsourcing neural network inference tasks to an untrusted cloud raises ...
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A Scalable Approach for PrivacyPreserving Collaborative Machine Learning
We consider a collaborative learning scenario in which multiple dataown...
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Secure Aggregation with Heterogeneous Quantization in Federated Learning
Secure model aggregation across many users is a key component of federat...
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Analog Lagrange Coded Computing
A distributed computing scenario is considered, where the computational ...
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ByzantineResilient Secure Federated Learning
Secure federated learning is a privacypreserving framework to improve m...
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PrivacyPreserving Distributed Learning in the Analog Domain
We consider the critical problem of distributed learning over data while...
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Coded Computing for Federated Learning at the Edge
Federated Learning (FL) is an exciting new paradigm that enables trainin...
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Minimax Lower Bounds for Transfer Learning with Linear and Onehidden Layer Neural Networks
Transfer learning has emerged as a powerful technique for improving the ...
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TurboAggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
Federated learning is gaining significant interests as it enables model ...
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Coded Computing for Boolean Functions
The growing size of modern datasets necessitates a massive computation i...
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Entangled Polynomial Codes for Secure, Private, and Batch Distributed Matrix Multiplication: Breaking the ”Cubic” Barrier
In distributed matrix multiplication, a common scenario is to assign eac...
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Edge Computing in the Dark: Leveraging ContextualCombinatorial Bandit and Coded Computing
With recent advancements in edge computing capabilities, there has been ...
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Harmonic Coding: An Optimal Linear Code for PrivacyPreserving GradientType Computation
We consider the problem of distributedly computing a general class of fu...
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TimelyThroughput Optimal Coded Computing over Cloud Networks
In modern distributed computing systems, unpredictable and unreliable in...
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CodedPrivateML: A Fast and PrivacyPreserving Framework for Distributed Machine Learning
How to train a machine learning model while keeping the data private and...
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Fitting ReLUs via SGD and Quantized SGD
In this paper we focus on the problem of finding the optimal weights of ...
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INTERPOL: Information Theoretically Verifiable Polynomial Evaluation
We study the problem of verifiable polynomial evaluation in the userser...
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Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy
We consider a distributed computing scenario that involves computations ...
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Polynomially Coded Regression: Optimal Straggler Mitigation via Data Encoding
We consider the problem of training a leastsquares regression model on ...
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Compressed Coded Distributed Computing
Communication overhead is one of the major performance bottlenecks in la...
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CommunicationAware Scheduling of Serial Tasks for Dispersed Computing
There is a growing interest in development of innetwork dispersed compu...
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Fundamental Resource Tradeoffs for Encoded Distributed Optimization
Dealing with the shear size and complexity of today's massive data sets ...
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Straggler Mitigation in Distributed Matrix Multiplication: Fundamental Limits and Optimal Coding
We consider the problem of massive matrix multiplication, which underlie...
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NearOptimal Straggler Mitigation for Distributed Gradient Methods
Modern learning algorithms use gradient descent updates to train inferen...
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Coded Fourier Transform
We consider the problem of computing the Fourier transform of highdimen...
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A. Salman Avestimehr
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