Adversarially Robust Optimization with Gaussian Processes
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Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...
In the framework of process optimization, measurements can be used to compensate for the effect of uncertainty. The method studied in this paper combines a process model and measurements to iteratively improve the operation of continuous processes. Unlike ...
Repeated failures as well as difficulties related to the implementation of new hydroelectric powerplants in industrialized countries illustrate the paradigm evolution which manages relationship between human society and nature. Problems resulting from thes ...
EPFL2007
,
Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...
The electrical discharge machining process (EDM) was discovered in the 1950s, and was then used essentially to destroy unrecoverable damaged screws. Since then, huge progress has been achieved in making this process reliable and able to perform the most co ...
A method that exploits an information theoretic framework to extract optimized audio features using video information is presented. A simple measure of mutual information (MI) between the resulting audio and video features allows the detection of the activ ...
In the framework of process optimization, the use of measurements to compensate the effect of uncertainty has become an active area of research. One of the ideas therein is to enforce optimality by tracking the necessary conditions of optimality (NCO track ...
Econometric models play an important role in transportation analysis. Estimating more and more complex models becomes problematic. The associated log-likelihood function is highly nonlinear and non concave and the comlexity of the model requires constraint ...
STRC 20062006
,
Econometric models play an important role in transportation analysis. Estimating more and more complex models becomes problematic. The associated log-likelihood function is highly nonlinear and non concave and the comlexity of the model requires constraint ...