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Using variable length representations for machine learning statistics

机译:使用可变长度表示法进行机器学习统计

摘要

The present disclosure provides methods and systems for using variable length representations of machine learning statistics. A method may include storing an n-bit representation of a first statistic at a first n-bit storage cell. A first update to the first statistic may be received, and it may be determined that the first update causes a first loss of precision of the first statistic as stored in the first n-bit storage cell. Accordingly, an m-bit representation of the first statistic may be stored at a first m-bit storage cell based on the determination. The first m-bit storage cell may be associated with the first n-bit storage cell. As a result, upon receiving an instruction to use the first statistic in a calculation, a combination of the n-bit representation and the m-bit representation may be used to perform the calculation.
机译:本公开提供了用于使用机器学习统计的可变长度表示的方法和系统。一种方法可以包括在第一n位存储单元处存储第一统计的n位表示。可以接收对第一统计的第一更新,并且可以确定第一更新导致第一统计的第一精度损失,如存储在第一n位存储单元中的那样。因此,可以基于该确定将第一统计的m位表示存储在第一m位存储单元处。第一m位存储单元可以与第一n位存储单元相关联。结果,在接收到在计算中使用第一统计量的指令时,可以使用n位表示和m位表示的组合来执行计算。

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