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Found 5 papers, 0 papers with code
Asynchronous Distributed Optimization with Delay-free Parameters
In contrast to alternatives, our algorithms can converge to the fixed point set of their synchronous counterparts using step-sizes that are independent of the delays.
Federated Learning for IoUT: Concepts, Applications, Challenges and Opportunities
Internet of Underwater Things (IoUT) have gained rapid momentum over the past decade with applications spanning from environmental monitoring and exploration, defence applications, etc.
Leakage Localization in Water Distribution Networks: A Model-Based Approach
Finally, assuming the existence of a single leak, for a network comprising of more than one pipe and assuming that the network has a tree structure, we provide a systematic procedure for determining the leak location, the leak exponent, and the leak constant
Delay-adaptive step-sizes for asynchronous learning
In this paper, we show that it is possible to use learning rates that depend on the actual time-varying delays in the system.
Communication-efficient Variance-reduced Stochastic Gradient Descent
Moreover, it is much more robust to quantization (in terms of maintaining the true minimizer and the convergence rate) than the state-of-the-art algorithms for solving distributed optimization problems.
