CONSTRAINED SEARCH: IMPROVE MULTI-OBJECTIVE NAS QUALITY BY FOCUS ON DEMAND

Aspects of the disclosure provide an evolutionary neural architecture search (ENAS) method. For example, the ENAS method can include steps (a) performing one or more evolutionary operations on an initial population of neural architectures to generate offspring neural architectures, (b) evaluating performance of each of the offspring neural architectures to obtain at least one evaluation value of the offspring neural architecture with respect to a performance metric, (c) adjusting the evaluation values of the offspring neural architectures based on at least one constraint on the evaluation values, (d) selecting at least one of the offspring neural architectures as a new population of neural architectures, and (e) outputting the new population of neural architectures as a last population of neural architectures when a stopping criterion is achieved, or (f) iterating steps (a) to (d) with the new population of neural architectures being taken as the initial population of neural architectures.