Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
This work provides a new perspective on descent directions for constrained optimization, potentially improving algorithms for problems in machine learning and operations research, though it appears incremental in refining existing methods.
The paper tackles the problem of understanding descent directions in constrained minimization, showing that the optimal local direction is the shadow of the projected negative gradient, and introduces Shadow-CG, a method combining Frank-Wolfe and shadow steps with linear convergence rates dependent on breakpoints in the projection curve.
Descent directions such as movement towards Descent directions, including movement towards Frank-Wolfe vertices, away-steps, in-face away-steps and pairwise directions, have been an important design consideration in conditional gradient descent (CGD) variants. In this work, we attempt to demystify the impact of the movement in these directions towards attaining constrained minimizers. The optimal local direction of descent is the directional derivative (i.e., shadow) of the projection of the negative gradient. We show that this direction is the best away-step possible, and the continuous-time dynamics of moving in the shadow is equivalent to the dynamics of projected gradient descent (PGD), although it's non-trivial to discretize. We also show that Frank-Wolfe (FW) vertices correspond to projecting onto the polytope using an "infinite" step in the direction of the negative gradient, thus providing a new perspective on these steps. We combine these insights into a novel Shadow-CG method that uses FW and shadow steps, while enjoying linear convergence, with a rate that depends on the number of breakpoints in its projection curve, rather than the pyramidal width. We provide a linear bound on the number of breakpoints for simple polytopes and present scaling-invariant upper bounds for general polytopes based on the number of facets. We exemplify the benefit of using Shadow-CG computationally for various applications, while raising an open question about tightening the bound on the number of breakpoints for general polytopes.