are seen to equal Here we used the expected log determinant of a Wishart random matrix and the log normalization constant of the Wishart distribution and respectively. The middle term of (20) eventually becomes With these changes, it is not hard to see that Q L is concave separately in GLYPH<22>$_{GLYPH<16>}$ and 6$_{GLYPH<16>}$ . The 24 GLYPH<0> H 2 f K log . 2 GLYPH<25> / GLYPH<0> D .! ; 7 / g GLYPH<0> ! 2 tr$^{[}$ 7 ( H 6$_{GLYPH<16>}$ C H ∑ h D 1 $^{(}$6$_{h}$ C .GLYPH<22>$_{GLYPH<16>}$ GLYPH<0> GLYPH<22>$_{h}$ /.GLYPH<22>$_{GLYPH<16>}$ GLYPH<0> GLYPH<22>$_{h}$ / > ) )] : (38) GLYPH<0> A$_{GLYPH<23>}$ $^{(}$S GLYPH<0> 1 $^{)}$C GLYPH<23> GLYPH<0> K GLYPH<0> 1 2 D .! ; 7 / GLYPH<0> ! 2 tr $^{(}$S GLYPH<0> $^{1}$7 ) (37) GLYPH<0> 1 2 $^{{}$log $^{[}$. 2 GLYPH<25> / $^{K}$j GLYPH<127>$_{0}$ j $^{]}$C tr $^{(}$GLYPH<127> GLYPH<0> 1 0 $^{[}$6$_{GLYPH<16>}$ C .GLYPH<22>$_{GLYPH<16>}$ GLYPH<0> GLYPH<12>$_{0}$/.GLYPH<22>$_{GLYPH<16>}$ GLYPH<0> GLYPH<12>$_{0}$/ > ] )} (36) (see, for example, Beal 2003). The new cross entropy terms for GLYPH<16> and GLYPH<127> work out to A$_{!}$ .7 / : D log$^{[}$2 ! K = $^{2}$GLYPH<25> K . K GLYPH<0> 1 /= 4 K ∏ i D 1 0$^{(}$ ! C 1 GLYPH<0> i 2 ) ] C ! 2 log j 7 j (35) D .! ; 7 / : D log $^{(}$2 $^{K}$j 7 j $^{)}$C K ∑ i D 1 9$^{(}$ ! C 1 GLYPH<0> i 2 ) (34) 1 2 log $^{[}$. 2 GLYPH<25> e / $^{K}$j 6$_{GLYPH<16>}$ j $^{]}$GLYPH<0> ! GLYPH<0> K GLYPH<0> 1 2 D .! ; 7 / C ! K 2 C A$_{!}$ $^{(}$7) : (33)