Unverified50% confidenceFactExact time
Temporal randomization during training allows the policy to learn from asynchronous, multi-frequency data without needing to align all measurements to a fixed time grid.
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50%
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Long-term
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10/12/2026
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Related Claims
UnverifiedFor small-sample time series scenarios, time series cross-validation is more reliable than randomly splitting the data into training and test sets.80% similarVerifiedDomain randomization technology randomly perturbs physical parameters (such as mass, friction coefficient, motor delay, etc.) during training, forcing the policy to learn to operate robustly under various conditions.79% similarUnverifiedDuring training, Chronos Policy applies temporal randomization to two things: randomly sampling which observations are used, and randomly deciding when the action chunk begins execution.79% similarUnverified实验表明按由易到难顺序喂给模型训练样本能加速收敛并学到更鲁棒的特征表示，性能优于随机打乱顺序的训练78% similarVerifiedDomain Randomization forces a policy to learn robustness to environmental changes by randomizing simulation parameters during training.78% similar
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