  We introduce a fast and accurate heuristic for adaptive tomography that
addresses many of the limitations of prior methods. Previous approaches were
either too computationally intensive or tailored to handle special cases such
as single qubits or pure states. By contrast, our approach combines the
efficiency of online optimization with generally applicable and well-motivated
data-processing techniques. We numerically demonstrate these advantages in
several scenarios including mixed states, higher-dimensional systems, and
restricted measurements.
