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Fully Convergent Projection-based Methods with Momentum under Nonconvex Geometric Constraints
Nonlinear optimization problems with complicated, nonconvex, yet geometrically structured constraints can be tackled by projected-gradient methods: under weak regularity assumptions, these approaches were recently proved to possess convergence properties to the strongest stationarity conditions. In
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