The industry’s push to rebrand animal experimentation failures as a communication issue ignores the systemic risks documented ...
Researchers from Zhejiang University and their collaborators have developed Qjump, a hybrid quantum-classical algorithm for ...
In the first ever Q4Bio Challenge, research teams sought to demonstrate scalable quantum algorithms for healthcare, with Algorithmiq's work alongside Cleveland Clinic and IBM earning $2 million Q4Bio ...
When someone asks ChatGPT to recommend a marketing agency, a financial advisor or a software platform, the response feels ...
In his doctoral thesis, Michael Roop develops numerical methods that allow finding physically reliable approximate solutions ...
Abstract: Recently, neural combinatorial optimization (NCO) methods have been prevailing for solving multiobjective combinatorial optimization problems (MOCOPs). Most NCO methods are based on the ...
Abstract: The manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial ...
ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
This repository provides implementation for SNBO (Scalable Neural Network-based Blackbox Optimization) — a novel method for efficient blackbox optimization using neural networks. It also includes code ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results