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The following pages link to The nonsmooth landscape of phase retrieval (Q5857359):

Displaying 19 items.

Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence (Q2067681) (← links)
Implicit regularization in nonconvex statistical estimation: gradient descent converges linearly for phase retrieval, matrix completion, and blind deconvolution (Q2189396) (← links)
Misspecified nonconvex statistical optimization for sparse phase retrieval (Q2425184) (← links)
Stochastic Model-Based Minimization of Weakly Convex Functions (Q4620418) (← links)
Phase Retrieval Algorithm via Nonconvex Minimization Using a Smoothing Function (Q4622358) (← links)
Low rank matrix recovery with adversarial sparse noise* (Q5030160) (← links)
The Estimation Performance of Nonlinear Least Squares for Phase Retrieval (Q5138944) (← links)
(Q5159422) (← links)
Nonconvex Robust Low-Rank Matrix Recovery (Q5217366) (← links)
Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems (Q5231692) (← links)
Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity (Q5233106) (← links)
Distributed Stochastic Inertial-Accelerated Methods with Delayed Derivatives for Nonconvex Problems (Q5863523) (← links)
Asymptotic Properties of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization (Q5868947) (← links)
Bregman Finito/MISO for Nonconvex Regularized Finite Sum Minimization without Lipschitz Gradient Continuity (Q5869813) (← links)
Sharp global convergence guarantees for iterative nonconvex optimization with random data (Q6046308) (← links)
Provable Phase Retrieval with Mirror Descent (Q6168333) (← links)
High probability bounds on AdaGrad for constrained weakly convex optimization (Q6649705) (← links)
Gradient descent provably escapes saddle points in the training of shallow ReLU networks (Q6655804) (← links)
Stochastic optimization over proximally smooth sets (Q6663114) (← links)