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Transfer Learning (TL)
Program Manager: Dr. Daniel Oblinger
Mission:
The Transfer Learning program seeks to solve the problem of reusing knowledge derived in one domain to help effect solutions in another domain. Adaptive systems, systems that respond to changes in their environment, stand to benefit significantly from the application of TL technology. Today's adaptive systems need to be trained for every new situation they encounter. This requires building new training data, which is the most expensive and most limiting aspect of deploying such systems. The TL program addresses this shortcoming by imbuing adaptive systems with the ability to encapsulate what they have learned and apply this knowledge to new situations. Thus, rather than having to be retrained for each new context, TL enables systems to leverage what they have already learned in order to be effective much sooner and with less effort spent on training. Early applications of TL technology include adaptive ISR systems, robotic vision and manipulation, and automated population of databases from unstructured text.
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