Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Kullback–Leibler (KL) divergence beten two mixture models is a fundamental primitive in many signal processing tasks. Since the KL divergence of mixtures does not admit a closed-form formula, it is in practice either estimated using costly Monte-Carlo stochastic integration or approximated.  present a fast and generic method that builds algorithmically closed-form lor and upper bounds on the entropy, the cross-entropy and the KL divergence of univariate mixtures.  illustrate the versatile method by reporting on our experiments for approximating the KL divergence beten Gaussian mixture models.
['Frank Nielsen', 'Ke Sun']
I am writing a research paper on a idea Guaranteed Bounds on the Kullback–Leibler Divergence of Univariate Mixtures
[{"from": "human", "value": "I am writing a research paper on a idea Guaranteed Bounds on the Kullback\u2013Leibler Divergence of Univariate Mixtures"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Kullback\u2013Leibler (KL) divergence beten two mixture models is a fundamental primitive in many signal processing tasks. Since the KL divergence of mixtures does not admit a closed-form formula, it is in practice either estimated using costly Monte-Carlo stochastic integration or approximated.  present a fast and generic method that builds algorithmically closed-form lor and upper bounds on the entropy, the cross-entropy and the KL divergence of univariate mixtures.  illustrate the versatile method by reporting on our experiments for approximating the KL divergence beten Gaussian mixture models."}]