Unverified50% confidenceBenchmarkExact time
The study claims to have improved the training speed of nonlinear RNNs on time series of chaotic dynamical systems by more than two orders of magnitude (>100×).
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10/1/2026
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Unverified由于相邻帧光流可在一次批量传递中完成计算,整体训练速度提升约2.7倍68% similarUnverified标准SVM(使用SMO等优化算法)的训练时间复杂度介于O(n²)到O(n³)之间,样本量从1000增加到10000理论耗时可能增加100到1000倍67% similarVerifiedMixed-precision training can typically increase training speed by 1.5–2 times and reduce VRAM usage by nearly half.63% similarUnverified混合精度训练在不显著损失模型精度的前提下,可将训练速度提升约2倍,显存占用降低近一半63% similarUnverifiedBidirectional joint training is equivalent to imposing implicit consistency regularization, analogous to a soft constraint on time-reversal symmetry.62% similar
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