Add a general sparse iterative solver: CGNR
This adds a new LinearOperator which implements symmetric
products of a matrix, and a new CGNR solver to leverage
CG to directly solve the normal equations. This also
includes a block diagonal preconditioner. In experiments
on problem-16, the non-preconditioned version is about
1/5 the speed of SPARSE_SCHUR, and the preconditioned
version using block cholesky is about 20% slower than
SPARSE_SCHUR.
diff --git a/internal/ceres/linear_solver.h b/internal/ceres/linear_solver.h
index d287813..5860ecc 100644
--- a/internal/ceres/linear_solver.h
+++ b/internal/ceres/linear_solver.h
@@ -154,7 +154,7 @@
// In either case, x is the vector that solves the following
// optimization problem.
//
- // arg min_x ||Ax -b||^2 + ||Dx||^2
+ // arg min_x ||Ax - b||^2 + ||Dx||^2
//
// Here A is a matrix of size m x n, with full column rank. If A
// does not have full column rank, the results returned by the
