Under the homoscedastic Gaussian assumption, it has been shown that Fisher’s linear discriminant analysis (FLDA) suffers from the class separation problem when the dimensionalit...
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
We introduce a new 3D shape descriptor which maps the surface features onto an arbitrary template surface using mean-value interpolation. A compact numerical shape descriptor is e...
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...