[optimization] implemented Google's FTRL-Proximal, adapted for the multiclass/multinomial case. It is L1 and L2 regularized, and should both encourage sparsity with the L1 penalty while being robust to collinearity of features due to the L2 penalty. Ref: https://research.google.com/pubs/archive/41159.pdf

src/matrix.h

@@ -19,6 +19,11 @@
 #warning "No CLBAS"
 #endif
 
+typedef enum {
+    MATRIX_DENSE,
+    MATRIX_SPARSE
+} matrix_type_t;
+
 #define MATRIX_INIT(name, type, type_name, array_type)                                                          \
     typedef struct {                                                                                            \
         size_t m, n;                                                                                            \