English(EN) Parallel Broyden Methods for Efficiently Evaluating Nonlinear State Space Models

新型布罗伊登方法增强状态空间模型评估

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-11 05:00

研究人员开发了一种使用布罗伊登方法的新型拟牛顿方法，用于高效评估非线性状态空间模型。该方法通过从轨迹割线导出的雅可比块的对角加低秩近似来捕获耦合项。该方法避免了自动微分，并且通过秩压缩与并行扫描兼容，证明了有限步内精确轨迹恢复。经验上，该方法在RNN、并行MCMC算法和去噪扩散模型等模型的收敛速度和并行执行方面显示出优势，尤其是在雅可比评估成本高或状态维度大的情况下。 AI

影响这种新方法通过提高计算效率，有可能加速RNN和扩散模型等复杂AI模型的训练和推理。

排序理由关于评估非线性状态空间模型的新算法方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Ian Christopher Tanoh, Scott W. Linderman · 2026-11-11 05:00

用于高效评估非线性状态空间模型的并行Broyden方法

arXiv:2611.13523v1 Announce Type: new Abstract: Nonlinear state space models are typically evaluated sequentially, limiting their ability to exploit modern parallel hardware. Recent work has shown that state space models can be evaluated in parallel by reformulating evaluation as…

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用于高效评估非线性状态空间模型的并行Broyden方法

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