In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
The Constraint-Based Agent (CBA) framework is a set of tools for designing, simulating, building, verifying, optimizing, learning and debugging controllers for agents embedded in a...
It has been widely advocated that software architecture an effective set of abstractions for engineering (families of) complex software systems. However, architectural concepts ar...
Sam Malek, Chiyoung Seo, Sharmila Ravula, Brad Pet...