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Found 5 papers, 0 papers with code
Maximal-Capacity Discrete Memoryless Channel Identification
Based on this capacity estimator, a gap-elimination algorithm termed BestChanID is proposed, which is oblivious to the capacity-achieving input distribution and is guaranteed to output the DMC with the largest capacity, with a desired confidence.
Private Aggregation in Wireless Federated Learning with Heterogeneous Clusters
Federated learning collaboratively trains a neural network on privately owned data held by several participating clients.
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.
Nested Gradient Codes for Straggler Mitigation in Distributed Machine Learning
Since the number of stragglers in practice is random and unknown a priori, tolerating a fixed number of stragglers can yield a sub-optimal computation load and can result in higher latency.
Cost-Efficient Distributed Learning via Combinatorial Multi-Armed Bandits
We consider the distributed SGD problem, where a main node distributes gradient calculations among $n$ workers.
