Learning to Shuffle: Block Reshuffling and Reversal Schemes for Stochastic Optimization
arXiv:2604.00260v1 Announce Type: new
Abstract: Shuffling strategies for stochastic gradient descent (SGD), including incremental gradient, shuffle-once, and random reshuffling, are supported by rigorous convergence analyses for arbitrary within-epoch…