This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
In this paper, we address the task of mapping high-level instructions to sequences of commands in an external environment. Processing these instructions is challenging--they posit...
S. R. K. Branavan, Luke S. Zettlemoyer, Regina Bar...
This paper presents a search algorithm for finding functions that are highly correlated with an arbitrary set of data. The functions found by the search can be used to approximate...