Department of Computer, Control and Management Engineering

The notion of "identifiability" underpins the active-set philosophy in optimization, and often manifests itself in variational formulations seeking low-dimensional structure from high-dimensional data.  Beyond the realm of convexity, identifiability remains a fundamental property, occurring generically in semi-algebraic optimization.  I illustrate its relevance for two simple and popular nonconvex algorithms:  alternating projections and a proximal algorithm for composite optimization.

Joint work with J. Bolte, A. Daniilidis, D. Drusvyatskiy and S. Wright