Federated learning (FL) typically relies on synchronous training, which ...
Due to the surge of cloud-assisted AI services, the problem of designing...
We consider the problem of coded computing where a computational task is...
Outsourcing neural network inference tasks to an untrusted cloud raises ...
We consider a collaborative learning scenario in which multiple data-own...
Secure model aggregation across many users is a key component of federat...
A distributed computing scenario is considered, where the computational ...
Secure federated learning is a privacy-preserving framework to improve
m...
We consider the critical problem of distributed learning over data while...
Federated Learning (FL) is an exciting new paradigm that enables trainin...
Transfer learning has emerged as a powerful technique for improving the
...
Federated learning is gaining significant interests as it enables model
...
The growing size of modern datasets necessitates a massive computation i...
In distributed matrix multiplication, a common scenario is to assign eac...
With recent advancements in edge computing capabilities, there has been ...
We consider the problem of distributedly computing a general class of
fu...
In modern distributed computing systems, unpredictable and unreliable
in...
How to train a machine learning model while keeping the data private and...
In this paper we focus on the problem of finding the optimal weights of ...
We study the problem of verifiable polynomial evaluation in the user-ser...
We consider a distributed computing scenario that involves computations ...
We consider the problem of training a least-squares regression model on ...
Communication overhead is one of the major performance bottlenecks in
la...
There is a growing interest in development of in-network dispersed compu...
Dealing with the shear size and complexity of today's massive data sets
...
We consider the problem of massive matrix multiplication, which underlie...
Modern learning algorithms use gradient descent updates to train inferen...
We consider the problem of computing the Fourier transform of
high-dimen...