$α$ -测地线偏散度
$α$-Geodesical Skew Divergence
摘要：
非对称偏斜发散通过将其中一个分布与另一个分布混合到由参数$λ$确定的程度来平滑该分布。这种发散是KL发散的近似，其不要求目标分布相对于源分布是绝对连续的。本文提出了斜散度的信息几何推广--$α$ -测地线斜散度，并研究了它的性质。
英文摘要：
The asymmetric skew divergence smooths one of the distributions by mixing it, to a degree determined by the parameter $λ$, with the other distribution. Such divergence is an approximation of the KL divergence that does not require the target distribution to be absolutely continuous with respect to the source distribution. In this paper, an information geometric generalization of the skew divergence called the $α$-geodesical skew divergence is proposed, and its properties are studied.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
