Abstract: Parallel Bayesian optimization is crucial for solving expensive black-box problems, yet batch acquisition strategies remain a challenge. To address this, we propose a novel parallel ...

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In this paper, we introduce a methodology to improve upon the ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

Peter the Great St. Petersburg Polytechnic University, St. Petersburg 195251, Russian Federation Academic University, Russian Academy of Sciences, St. Petersburg 194021, Russian Federation ...

SEOs are prioritizing AI search tactics like schema and citations, even as revenue impact remains small and measurement is messy. SEOs (and their bosses) are rapidly adopting AI search optimization, ...

This repository contains experiment that implements Bayesian Optimization (BO) techniques for Conditional Value-at-Risk (CVaR)-based portfolio optimization, inspired by the research paper "Bayesian ...