We present a cognitive model that bridges work in analogy and category learning. The model, Building Relations through Instance Driven Gradient Error Shifting (BRIDGES), extends A...
e about image features can be expressed as a hierarchical structure called a Type Abstraction Hierarchy (TAH). TAHs can be generated automatically by clustering algorithms based on...
Wesley W. Chu, Alfonso F. Cardenas, Ricky K. Taira
This work investigates the use of nonlinear dependencies in natural image sequence statistics to learn higher-order structures in natural videos. We propose a two-layer model that...
While low-dimensional image representations have been very popular in computer vision, they suffer from two limitations: (i) they require collecting a large and varied training se...
We consider history independent data structures as proposed for study by Naor and Teague [3]. In a history independent data structure, nothing can be learned from the memory repre...
Jason D. Hartline, Edwin S. Hong, Alexander E. Moh...