1. A method, comprising: optimizing one or more parameters of a natural language processing system so as to improve a measure of quality of an output of the natural language processing system for a first type of data processed by the natural language processing system while maintaining a given measure of quality of an output of the natural language processing system for a second type of data processed by the natural language processing system, wherein the optimizing comprises computing a conditional value at risk metric.
1. A method, comprising: optimizing one or more parameters of a natural language processing system so as to improve a measure of quality of an output of the natural language processing system for a first type of data processed by the natural language processing system while maintaining a given measure of quality of an output of the natural language processing system for a second type of data processed by the natural language processing system, wherein the optimizing comprises computing a conditional value at risk metric. 5. The method of claim 1 , wherein the conditional value at risk computing step further comprises obtaining one or more input data sets.