15 citations · 17 across the 3 of their papers we have counts for
3 papers
Deep Reinforcement Learning for Dexterous Manipulation with Concept Networks
Aditya Gudimella, Ross Story, Matineh Shaker +4
Deep reinforcement learning yields great results for a large array of problems, but models are generally retrained anew for each new problem to be solved. Prior learning and knowle…
Subject-Specific Abnormal Region Detection in Traumatic Brain Injury Using Sparse Model Selection on High Dimensional Diffusion Data
Matineh Shaker, Deniz Erdogmus, Jennifer Dy +1
We present a method to estimate a multivariate Gaussian distribution of diffusion tensor features in a set of brain regions based on a small sample of healthy individuals, and use…
Manifold unwrapping using density ridges
Jonas Nordhaug Myhre, Matineh Shaker, Devrim Kaba +2
Research on manifold learning within a density ridge estimation framework has shown great potential in recent work for both estimation and de-noising of manifolds, building on the…