Paper solves open problem of first-order algorithms for filtering-clustering models.
problem Understanding convergence property of first-order algorithms for filtering-clustering models.
method Identifies a global error bound condition and designs a generalized dual gradient ascent algorithm.
result Proposes optimal first-order algorithms in deterministic, finite-sum, and online settings.