This work investigates the design of sparse secret sharing schemes that
...
This paper considers the problem of outsourcing the multiplication of tw...
Federated learning collaboratively trains a neural network on privately ...
In distributed machine learning, a central node outsources computational...
We consider gradient coding in the presence of an adversary, controlling...
We consider distributed learning in the presence of slow and unresponsiv...
We consider the problem of correcting insertion and deletion errors in t...
We consider the setting where a master wants to run a distributed stocha...
We consider the problem of maintaining sparsity in private distributed
s...
We consider the problem of designing a coding scheme that allows both
sp...
We consider the distributed stochastic gradient descent problem, where a...
Consider the problem of designing secure and private codes for distribut...
We consider the problem of constructing codes that can correct deletions...
We study codes that can detect the exact number of deletions and inserti...
We consider the problem of reliable communication over a network contain...
Motivated by applications in machine learning and archival data storage,...
This paper investigates the problem of correcting multiple criss-cross
d...
We consider the problem of designing codes with flexible rate (referred ...
This paper studies the problem of constructing codes correcting deletion...
We consider the problem of designing rateless coded private distributed
...
We consider the setting where a master wants to run a distributed stocha...
Consider the communication efficient secret sharing problem. A dealer wa...
Edge computing is emerging as a new paradigm to allow processing data ne...
Edge computing is emerging as a new paradigm to allow processing data at...
We consider distributed gradient descent in the presence of stragglers.
...
We consider the problem of designing private information retrieval (PIR)...
We consider the setting of a Master server, M, who possesses confidentia...