Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

An Inexpensive Alternative to CS Photoshop & Bridge: Archival Master Image Capture and Batch Derivative Creation in Canon Scan Gear & Adobe Photoshop Elements 7

This presentation was made at the Connecticut State Library Service Center, Willimantic, CT, April 14, 2009. It focused on digital capture workflows for both archival and derivative image creation using accepted current standards. Tools used were inexpensive by choice and focused towards the needs of small to mid-sized cultural heritage institutions who wish to begin digital capture in their own facilities.

Concentration profiles in batch fermentation of hydrolyzed lignocellulose

Experimental data was obtained for profiling changes in concentrations of two inhibiting compounds in batch fermentation of a synthesized liquor resembling hydrolyzed lignocellulose, a furan (furfural) and a phenolic compound (vanillin), along with standard fermentation data, i.e. substrate, biomass and ethanol concentrations. The initial inhibitor concentrations and fermentation temperatures in the 18 experiments were varied according to a two-level complete center composite experimental design. Based upon these observed variations in the fermentative behavior, the fermentation kinetics were modeled, as published in the corresponding article, including microbial conversion rates of the inhibitive compounds into their less toxic derivatives.