https://proceedings.neurips.cc/paper_files/paper/2012/hash/05311655a15b75fab86956663e1819cd-Abstract.html ...

This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...

Abstract: Bayesian optimization (BO) is a powerful surrogate-assisted algorithm for solving expensive black-box optimization problems. While BO was developed for centralized optimization, the ...

Abstract: 5G millimeter-wave (mmWave) communications are essential for enabling ultra-high-speed, low-latency wireless connectivity to support data-intensive applications. However, the highly ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

In the shown examples from the field of shape optimization and parameter reconstruction, Bayesian optimization, mainly known from machine learning applications, obtains significantly better results in ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

US-based Food System Innovations (FSI) has launched its Food Intelligence Lab to build an open-source AI infrastructure that ...

Yiting Hu, Lingjie Duan Proofs of Ownership for Machine Learning Models Ran Canetti, Shafi Goldwasser, Or Zamir Forensic Trajectory Signatures for Agent Memory Poisoning Detection Jun Wen Leong ...