Abstract: This paper introduces an Outer Approximation (OA) method for solving discrete AC Optimal Power Flow (OPF) problems that account for switching decisions. The OPF problem is formulated via the ...

Abstract: Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-and-error in the environment ...

Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This paper explores the use ...

The travelling salesman problem (TSP) remains one of the most challenging NP‐hard problems in combinatorial optimisation, with significant implications for logistics, network design and route planning ...

This repository provides the official implementation of QSVD, a method for efficient low-rank approximation that unifies Query-Key-Value (QKV) weight compression in low-precision Vision-Language ...

This valuable study links psychological theories of chunking with a physiological implementation based on short-term synaptic plasticity and synaptic augmentation. The theoretical derivation for ...

Given the current state of practice and visions for the future (including AI), certain practices should be reevaluated. This ...

The Cheeseburger Omelet sounds like a dare but tastes like genius – ground beef, cheese, onions, mushrooms, and tomatoes folded into fluffy eggs. For spice enthusiasts, the Babyducks Chopped Pork ...