The outer objective function is a classical strongly convex function which may not be smooth. Motivated by the smoothing approaches, we modify the classical bi-level gradient sequential averaging ...

Abstract: In this paper, we study asymptotic behaviors of continuous-time and discrete-time gradient flows of a “lower-unbounded” convex function on a Hadamard manifold, particularly, their ...

Interestingly, many traditional non-convex objectives, including partially convex problems, matrix factorizations, and neural networks, fall within these subclasses. Then, we propose gradient methods ...

In the new paper Optimistic Meta-Gradients, a DeepMind research team explores the connection between gradient-based meta-learning and convex optimization, demonstrating that optimism (a prediction of ...

Karimi, S. , & Vavasis, S. A. . (Accepted). Nonlinear conjugate gradient for smooth convex functions. Mathematical Programming - Computation. Retrieved from https ...

The project involves the implementation of classical optimization methods such as gradient descent and penalty methods, evolutionary algorithms such as genetic algorithm, particle swarm optimization, ...

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