Diego Munoz
In 'Beta Parameters for Unidirectional Interpretation of Bayesian Optimization', Diego Munoz dives into the intricate mathematical underpinnings behind how Bayesian optimization works but focusing more on what role beta parameters play in influencing our unidirectional lean. A probabilistic approach combined with real-life examples, it offers a more thorough examination of what to expect when indexes are implemented on complex systems. Munoz’s work is an invaluable source of information for academics, mathematicians and data scientists wishing to deep delve further into optimization strategies.
