Can someone help me to answer my question: if DAAL is good for convex constrained optimization?
As stated in the article ( https://software.intel.com/en-us/daal-programming-guide-objective-function), the proximal operator there could be used for non-smooth part of objective function, and the example (https://software.intel.com/en-us/daal-programming-guide-logistic-loss) shows this for L1 regularization. On the other hand, if non-smooth part M(theta) is just an indicator (characteristic) function of some convex set (constraints) , the proximal operator is exactly projection operator.
Is it possible to pass this projection operator to objective function object to handle convex constraints in that way?
Thanks! Your help is much appreciated,