We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
Peng Zang, Peng Zhou, David Minnen, Charles Lee Is...
Abstract. A base problem in Web information extraction is to find appropriate queries for informative nodes in trees. We propose to learn queries for nodes in trees automatically ...
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
Aiming to clarify the convergence or divergence conditions for Learning Classifier System (LCS), this paper explores: (1) an extreme condition where the reinforcement process of ...
We define a process called congealing in which elements of a dataset (images) are brought into correspondence with each other jointly, producing a data-defined model. It is based ...
Erik G. Miller, Nicholas E. Matsakis, Paul A. Viol...