210 results — page 1 of 11
The fine-tuning of Large Language Models (LLMs) has enabled them to recently achieve milestones in natural language processing applications. The emergenc...
A challenge in aircraft design optimization is the presence of non-computable, so-called hidden, constraints that do not return a value in certain regions of...BibTeX reference
In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...BibTeX reference
This paper introduces a new step to the Direct Search Method (DSM) to strengthen its convergence analysis. By design, this so-called covering step may e...BibTeX reference
In this work, we propose a non-intrusive and training free method to detect behind-the-meter (BTM) electric vehicle (EV) charging events from the data measur...BibTeX reference
The Harwell Subroutine Library (HSL) is a renowned suite of efficient and robust numerical algorithms designed to tackle complex mathematical problems such a...BibTeX reference
Monte Carlo (MC) is widely used for the simulation of discrete time Markov chains. We consider the case of a
\(d\)-dimensional continuous state space and w...
This work introduces a novel multi-fidelity blackbox optimization algorithm designed to alleviate the resource-intensive task of evaluating infeasible points...BibTeX reference
Complexity of trust-region methods with unbounded Hessian approximations for smooth and nonsmooth optimization
We develop a worst-case evaluation complexity bound for trust-region methods in the presence of unbounded Hessian approximations. We use the algorithm of Ar...BibTeX reference
We consider the set of graphs that can be constructed from a one-vertex graph by repeatedly adding a clique or a stable set linked to all or none of the vert...BibTeX reference
Reinforcement learning (RL) for partially observable Markov decision processes (POMDPs) is a challenging problem because decisions need to be made based on t...BibTeX reference
Price-based strategies for mitigating electric vehicle-induced overloads on distribution systems
This paper first introduces a computationally efficient approach for conducting a time-series impact analysis of electric vehicle (EV) charging on the loadin...BibTeX reference
Risk averse constrained blackbox optimization under mixed aleatory/epistemic uncertainties
This paper addresses risk averse constrained optimization problems where the objective and constraint functions can only be computed by a blackbox subject to...BibTeX reference
Evolution of high throughput satellite systems: Vision, requirements, and key technologies
High throughput satellites (HTS), with their digital payload technology, are expected to play a key role as enablers of the upcoming 6G networks. HTS are mai...BibTeX reference
PLSR1: A limited-memory partitioned quasi-Newton optimizer for partially-separable loss functions
Improving neural network optimizer convergence speed is a long-standing priority. Recently, there has been a focus on quasi-Newton optimization methods, whi...BibTeX reference
Historically, the training of deep artificial neural networks has relied on parallel computing to achieve practical effectiveness. However, with the increas...BibTeX reference
We introduce an iterative solver named MINARES for symmetric linear systems
\(Ax \approx b\), where
\(A\) is possibly singular.
MINARES is based on t...
Corrigendum: A proximal quasi-Newton trust-region method for nonsmooth regularized optimization
The purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...BibTeX reference
We develop a trust-region method for minimizing the sum of a smooth term
\(f\) and a nonsmooth term
\(h\), both of which can be nonconvex.