Feb. 13, 2024, 5:44 a.m. | Yihang Shen Carl Kingsford

cs.LG updates on arXiv.org arxiv.org

Bayesian Optimization (BO) is a method for globally optimizing black-box functions. While BO has been successfully applied to many scenarios, developing effective BO algorithms that scale to functions with high-dimensional domains is still a challenge. Optimizing such functions by vanilla BO is extremely time-consuming. Alternative strategies for high-dimensional BO that are based on the idea of embedding the high-dimensional space to the one with low dimension are sensitive to the choice of the embedding dimension, which needs to be pre-specified. …

algorithms bayesian box challenge cs.lg domains functions optimization scale stat.ml strategies via

Research Scholar (Technical Research)

@ Centre for the Governance of AI | Hybrid; Oxford, UK

HPC Engineer (x/f/m) - DACH

@ Meshcapade GmbH | Remote, Germany

Data Engineering Director-Big Data technologies (Hadoop, Spark, Hive, Kafka)

@ Visa | Bengaluru, India

Senior Data Engineer

@ Manulife | Makati City, Manulife Philippines Head Office

GDS Consulting Senior Data Scientist 2

@ EY | Taguig, PH, 1634

IT Data Analyst Team Lead

@ Rosecrance | Rockford, Illinois, United States