Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
We describe an algorithm for similar-image search which
is designed to be efficient for extremely large collections of
images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
— Legged robots represent great promise for transport in unstructured environments. However, it has been difficult to devise motion planning strategies that achieve a combinatio...
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...