Stochastic Gradient Descent (SGD) algorithms are widely used in optimizi...
Gradient clipping is a popular modification to standard (stochastic) gra...
We study stochastic optimization with linearly correlated noise. Our stu...
Gradient tracking (GT) is an algorithm designed for solving decentralize...
We study the asynchronous stochastic gradient descent algorithm for
dist...
Decentralized learning provides an effective framework to train machine
...
We consider decentralized machine learning over a network where the trai...
In decentralized machine learning, workers compute model updates on thei...
We consider decentralized stochastic variational inequalities where the
...
Decentralized training of deep learning models enables on-device learnin...
Decentralized optimization methods enable on-device training of machine
...
Decentralized stochastic optimization methods have gained a lot of atten...
Decentralized training of deep learning models is a key element for enab...
We consider decentralized stochastic optimization with the objective fun...
Coordinate descent with random coordinate selection is the current state...