Abstract We present a matrix-free line search algorithm for large-scale equality constrained optimization that allows for inexact step computations. For sufficiently convex problem...
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
Scheme includes a simple yet powerful macro mechanism. Using macros, programmers can easily extend the language with new kinds of expressions and definitions, thus abstracting ove...
Abstract. This paper introduces a new software polymorphism technique that randomizes program data structure layout. This technique will generate different data structure layouts f...
Abstract. Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective...
Philip E. Gill, Walter Murray, Michael A. Saunders