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Found 2 papers, 1 papers with code
Distributed Stochastic Gradient Descent with Cost-Sensitive and Strategic Agents
During each round, each agent samples a minibatch of training data and sends his gradient update.
Coverage-Based Designs Improve Sample Mining and Hyper-Parameter Optimization
Sampling one or more effective solutions from large search spaces is a recurring idea in machine learning, and sequential optimization has become a popular solution.
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