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Found 5 papers, 2 papers with code
Approximate Gradient Coding for Privacy-Flexible Federated Learning with Non-IID Data
This work focuses on the challenges of non-IID data and stragglers/dropouts in federated learning.
Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load
Considering this model, we construct a novel scheme that adapts both the number of workers and the computation load throughout the run-time of the algorithm.
Adaptive Stochastic Gradient Descent for Fast and Communication-Efficient Distributed Learning
Moreover, the results also show that the adaptive version is communication-efficient, where the amount of communication required between the master and the workers is less than that of non-adaptive versions.
Adaptive Distributed Stochastic Gradient Descent for Minimizing Delay in the Presence of Stragglers
One solution studied in the literature is to wait at each iteration for the responses of the fastest $k<n$ workers before updating the model, where $k$ is a fixed parameter.
Guess & Check Codes for Deletions, Insertions, and Synchronization
We consider the problem of constructing codes that can correct $\delta$ deletions occurring in an arbitrary binary string of length $n$ bits.
Information Theory Information Theory
