Lines Matching refs:Problem
47 class Problem;
60 // Default constructor that sets up a generic sparse problem.
141 // with a message describing the problem.
162 // is contracted and the model optimization problem is solved
191 // maximum rank. The best choice usually requires some problem
210 // performance for certain classes of problem, which is why it is disabled
212 // sensitivity of the problem to different parameters varies significantly,
236 // Solving the line search problem exactly is computationally
528 // If your problem does not have this property (or you do not know),
539 // e.g., consider the following regression problem
550 // eliminate the variables a_1 and a_2 from the problem all
552 // squares problem and the most famous algorithm for solving them
557 // missing data problem. There the corresponding algorithm is
569 // computed for the whole problem (a_1, a_2, b_1, b_2, c_1) and
575 // for the full problem, and then use it as the starting point to
653 // region problem. Useful for testing and benchmarking. If empty
749 // Cost of the problem (value of the objective function) before
753 // Cost of the problem (value of the objective function) after the
811 // Number of parameter blocks in the problem.
817 // Dimension of the tangent space of the problem (or the number of
818 // columns in the Jacobian for the problem). This is different
823 // Number of residual blocks in the problem.
826 // Number of residuals in the problem.
829 // Number of parameter blocks in the problem after the inactive
834 // Number of parameters in the reduced problem.
837 // Dimension of the tangent space of the reduced problem (or the
839 // problem). This is different from num_parameters_reduced if a
840 // parameter block in the reduced problem is associated with a
844 // Number of residual blocks in the reduced problem.
847 // Number of residuals in the reduced problem.
860 // region problem.
864 // trust region problem. This number is not equal to
873 // problem structure is not compatible with the linear solver
887 // ordering, or if the problem contains some constant or inactive
896 // of the optimization and the problem structure was such that
897 // they were actually performed. e.g., in a problem with just one
909 // ordering, or if the problem contains some constant or inactive
926 // problem.
955 // Once a least squares problem has been built, this function takes
956 // the problem and optimizes it based on the values of the options
961 Problem* problem,
967 Problem* problem,
