18 citations · 35 across the 13 of their papers we have counts for
4 papers · 1 filter
ByGARS: Byzantine SGD with Arbitrary Number of Attackers
Jayanth Regatti, Hao Chen, Abhishek Gupta
We propose two novel stochastic gradient descent algorithms, ByGARS and ByGARS++, for distributed machine learning in the presence of any number of Byzantine adversaries. In these…
Convergence of Recursive Stochastic Algorithms using Wasserstein Divergence
Abhishek Gupta, William B. Haskell
This paper develops a unified framework, based on iterated random operator theory, to analyze the convergence of constant stepsize recursive stochastic algorithms (RSAs). RSAs use…
Learning in Markov Decision Processes under Constraints
Rahul Singh, Abhishek Gupta, Ness B. Shroff
We consider reinforcement learning (RL) in Markov Decision Processes in which an agent repeatedly interacts with an environment that is modeled by a controlled Markov process. At e…
Some Limit Properties of Markov Chains Induced by Stochastic Recursive Algorithms
Abhishek Gupta, Hao Chen, Jianzong Pi +1
Recursive stochastic algorithms have gained significant attention in the recent past due to data driven applications. Examples include stochastic gradient descent for solving large…