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natural parameters or covariance parameters for variational approximations #19

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thangbui opened this issue Jun 5, 2017 · 0 comments

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@thangbui
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thangbui commented Jun 5, 2017

Investigating ways to parameterise the variational approximations in the uncollapsed variational bound or approximate Power-EP energy, in particular q(u) = N(u; 0, LL^T) or q(u) = N_{natural}(u; \theta_1; Kuu^{-1} + \theta_2) -- which is faster or results in better learning curves etc?

See figure 1 here http://papers.nips.cc/paper/5559-decoupled-variational-gaussian-inference.pdf

thangbui added a commit that referenced this issue Jun 8, 2017
thangbui added a commit that referenced this issue Jun 8, 2017
… seeing faster convergence with the variance parameterisation
thangbui added a commit that referenced this issue Jun 12, 2017
thangbui added a commit that referenced this issue Jul 25, 2017
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