A Unified Learning Scheme: Bayesian-Kullback Ying-Yang Machine

Part of Advances in Neural Information Processing Systems 8 (NIPS 1995)

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Lei Xu


A Bayesian-Kullback learning scheme, called Ying-Yang Machine, is proposed based on the two complement but equivalent Bayesian representations for joint density and their Kullback divergence. Not only the scheme unifies existing major supervised and unsu(cid:173) pervised learnings, including the classical maximum likelihood or least square learning, the maximum information preservation, the EM & em algorithm and information geometry, the recent popular Helmholtz machine, as well as other learning methods with new variants and new results; but also the scheme provides a number of new learning models.