广义贝叶斯预测密度算子
Generalized Bayesian predictive density operators
摘要：
最近，量子贝叶斯预测问题由Tanaka和Komaki（2005）提出。结果表明，贝叶斯预测密度算子是最好的预测密度算子时，我们评估他们使用的平均量子相对熵的基础上的先验分布。在本文中，我们采用量子α发散作为更广泛的一类损失函数。广义贝叶斯预测密度算子的定义和证明是最好的所有未知密度算子的估计。
英文摘要：
Recently the quantum Bayesian prediction problem was formulated by Tanaka and Komaki (2005). It is shown that Bayesian predictive density operators are the best predictive density operators when we evaluate them by using the averaged quantum relative entropy based on a prior distribution. In the present paper, we adopt the quantum alpha-divergence as a wider class of loss function. The generalized Bayesian predictive density operator is defined and shown to be best among all the estimates of the unknown density operator.
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。
