1 / 4

Budgeted Optimization with Concurrent Stochastic-Duration Experiments

This paper presents a novel approach in Bayesian Optimization (BO) to tackle the challenge of maximizing an unknown function through costly experiments. Traditional BO methods evaluate one experiment at a time, but our extended model allows for concurrent experimentation and accounts for uncertainties in experiment durations. We propose both offline and online scheduling methods for initiating experiments, targeting efficient use of a total experimental budget within a defined time horizon. This work is particularly relevant for domains with stochastic experiment durations, enhancing performance in real-world applications.

jake
Download Presentation

Budgeted Optimization with Concurrent Stochastic-Duration Experiments

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Budgeted Optimization with Concurrent Stochastic-Duration Experiments JavadAzimi, Alan Fern, Xiaoli Fern Oregon State University NIPS 2011

  2. Bayesian Optimization (BO) • Goal: Maximize an unknown function f by requesting a small set of function evaluations (experiments)—experiments are costly • BO assumes prior over f – select next experiment based on posterior • Traditional BO selects one experiment at a time Gaussian Process Surface Current Experiments Select Single/multiple Experiment Run Experiment(s)

  3. Extended BO Model Many domains include: • Ability to run concurrent experiments • Allowed to run a maximum of lconcurrent experiments • Uncertainty about experiment durations • Experiments have stochastic durations with known distribution P • Total experimental budget n • Experimental time horizon h Current BO models do not model these domain features

  4. Proposed Solution • Problem: • Schedule when to start new experiments and which ones to start. • Proposed Solutions: • Offline Schedule: The start times have been defined before starting running experiments • Online Schedule: The start times determine at each time step Poster Number: W052

More Related