**Multi-class Discriminant
Kernel Learning via Convex Programming**

By Jieping Ye, Shuiwang Ji, and Jianhui Chen. Journal of Machine Learning Research, 9(Apr):719-758, 2008.

Source codes in MATLAB:

- Binary-class case
- SDP1 (Kernel learning by Semi-definite
Programming, with regularization parameter fixed at 0.0005 in our experiments)
- SDP2 (Joint kernel and
regularization parameters learning by Semi-definite Programming)
- QCQP1 (Kernel learning by Quadratically Constrained Quadratic programming, with
regularization parameter fixed at 0.0005 in our experiments)
- QCQP2 (Joint kernel and
regularization parameters learning by Quadratically
Constrained Quadratic programming)
- SILP1 (Kernel learning by Semi-infinite
Linear Programming with regularization parameter fixed at 0.0005 and
tolerance parameter fixed at 0.0005 in our experiments)
- SILP2 (Joint kernel and regularization
parameters learning by Semi-infinite Linear Programming)
- Multi-class case
- SDP1 (Kernel learning by
Semi-definite Programming, with regularization parameter fixed at 0.0005
in our experiments)
- SDP2 (Joint kernel and
regularization parameters learning by Semi-definite Programming)
- QCQP1 (Kernel learning by Quadratically Constrained Quadratic programming, with
regularization parameter fixed at 0.0005 in our experiments)
- QCQP2 (Joint kernel and
regularization parameters learning by Quadratically
Constrained Quadratic programming)
- SILP1 (Kernel learning by Semi-infinite
Linear Programming with regularization parameter fixed at 0.0005 and
tolerance parameter fixed at 0.0005 in our experiments)
- SILP2 (Joint kernel and regularization
parameters learning by Semi-infinite Linear Programming)