Found 1874 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

Nearly optimal first-order methods for convex optimization under gradient norm measure: An adaptive regularization approach

In the development of first-order methods for smooth (resp., composite) convex optimization problems minimizing smooth functions, the gradient (resp., gradient mapping) norm is a fundamental optimality measure for which a regularization technique of first-order methods is known to be nearly optimal. Expand abstract.
59 days ago
4/10 relevant
arXiv

What do QAOA energies reveal about graphs?

Quantum Approximate Optimization Algorithm (QAOA) is a hybrid classical-quantum algorithm to approximately solve NP optimization problems such as MAX-CUT. Expand abstract.
59 days ago
4/10 relevant
arXiv

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Decomposition Methods

To tackle such large scale problems, we propose two decomposition methods, whether handling the coupling constraints by prices or by resources. Expand abstract.
63 days ago
9/10 relevant
arXiv

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Application to Microgrid Management

Moreover, the decomposition methods are much faster than the SDDP method in terms of computation time, thus allowing to tackle problem instances incorporating more than 60 state variables in a Dynamic Programming framework. Expand abstract.
63 days ago
7/10 relevant
arXiv

Convolutional Neural Network-based Topology Optimization (CNN-TO) By Estimating Sensitivity of Compliance from Material Distribution

This paper proposes a new topology optimization method that applies a convolutional neural network (CNN), which is one deep learning technique for topology optimization problems. Expand abstract.
63 days ago
7/10 relevant
arXiv

Distributed Online Optimization with Long-Term Constraints

We consider distributed online convex optimization problems, where the distributed system consists of various computing units connected through a time-varying communication graph. Expand abstract.
66 days ago
7/10 relevant
arXiv

First order optimization methods based on Hessian-driven Nesterov accelerated gradient flow

Furthermore, accelerated splitting algorithms for composite optimization problems are also developed. Expand abstract.
67 days ago
4/10 relevant
arXiv

On local quasi efficient solutions for nonsmooth vector optimization

We are interested in local quasi efficient solutions for nonsmooth vector optimization problems under new generalized approximate invexity assumptions. Expand abstract.
68 days ago
4/10 relevant
arXiv

TSSOS: A Moment-SOS hierarchy that exploits term sparsity

Our theoretical framework is then applied to compute lower bounds for polynomial optimization problems either randomly generated or coming from the networked systems literature. Expand abstract.
68 days ago
4/10 relevant
arXiv

Active strict saddles in nonsmooth optimization

We argue that the strict saddle property may be a realistic assumption in applications, since it provably holds for generic semi-algebraic optimization problems. Expand abstract.
71 days ago
4/10 relevant
arXiv