Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
"Assuming that you want to learn C++, why should you read this book rather than any of dozens of other introductory C++ books? One difference between this book and other intro...
We propose a novel method for temporally and spatially corresponding moving objects by automatically learning the relevance of the objects' appearance features to the task of...
Mahesh Saptharishi, John B. Hampshire II, Pradeep ...
We propose a hybrid body representation that represents each typical pose by both template-like view information and part-based structural information. Specifically, each body par...