Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
One time-consuming task in the development of software is debugging. Recent work in fault localization crosschecks traces of correct and failing execution traces, it implicitly se...
A Local Linear Embedding (LLE) module enhances the performance of two Evolutionary Computation (EC) algorithms employed as search tools in global optimization problems. The LLE em...
In our prior work, we presented a highly effective local search based heuristic algorithm called the Largest Expanding Sweep Search (LESS) to solve the minimum energy broadcast (M...