Implicit Bias of Gradient-Based Learning Under Non-Convex Constraints.
This article derives a projected gradient flow characterized by tangent and normal cone decompositions, which capture the local geometry of the constraint set and shows that constraint geometry continuously filters gradient directions along the optimization trajectory, leading to a trajectory-dependent implicit regularization effect without modifying the objective function.