Editing Semidefinite embedding (section)

'''Maximum Variance Unfolding (MVU)''', also known as '''Semidefinite Embedding''' (SDE), is an [[algorithm]] in [[computer science]] that uses [[semidefinite programming]] to perform [[non-linear dimensionality reduction]] of high-dimensional [[coordinate vector|vector]]ial input data.<ref>{{Harvnb|Weinberger, Sha and Saul|2004a}}</ref><ref>{{Harvnb|Weinberger and Saul|2004b}}</ref><ref>{{Harvnb|Weinberger and Saul|2006}}</ref>

It is motivated by the observation that [[Kernel principal component analysis|kernel Principal Component Analysis]] (kPCA) does not reduce the data dimensionality,<ref>{{Harvnb|Lawrence|2012|loc=page 1612}}</ref> as it leverages the [[Kernel trick]] to non-linearly map the original data into an [[inner-product space]].