Feb 1, 2023 · We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of ...
Jul 25, 2023 · My talk will explore analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems for designing a ...
Feb 1, 2023 · Abstract. We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new ...
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Abstract: This paper introduces a novel technique for nonlinear acceleration of first-order methods for constrained convex optimization.
Abstract. We introduce a class of first-order methods for smooth constrained optimization that are based on an analogy to non-smooth dynamical systems.
The method generates a sequence of strictly feasible points. Two techniques are used to maintain feasibility while achieving robust convergence behavior. First, ...
This work presents an adaptive superfast proximal augmented Lagrangian (AS-PAL) method for solving linearly-constrained smooth nonconvex composite ...
Abstract. Motivated by big data applications, first-order methods have been extremely popular in recent years. However, naive gradient methods generally ...
Feb 1, 2023 · We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of ...
This paper considers a class of convex-concave bilinear saddle point problems and proposes an accelerated first-order continuous-time algorithm. We design the ...