Procedure calls have long been recognized as an impediment to performance in compiled code. This happens because procedure calls hide information from the compiler. Interprocedural constant propagation attempts to discover ...

Two classes of primal-dual interior-point methods for nonlinear programming are studied. The first class corresponds to a path-following Newton method formulated in terms of the nonnegative variables rather than all primal ...

Programmers rely on the correctness of their tools. Semanticists have long studied the correctness of compilers, but we make the case that other tools deserve semantic models, too, and that using these models can help in ...

This work concerns efficiently solving a class of nonlinear integer programming problems: min $\{f(x)$: $x \in \{0,1\}\sp{n}\}$ where $f(x)$ is a general nonlinear function. The notion of subgradient for the objective ...

This thesis presents a new method of myoelectric signal recognition. Myoelectric signals are electric signals generated by the motion of a person's muscle and can be used as control input for prosthetic hands. It uses ...

This thesis considers duality properties and their application to the sequential gradient-restoration algorithms (SGRA) for optimal control problems. Two problems are studied: (P1) the basic problem and (P2) the general ...

The deficiency of the widely used LQG method is that it depends heavily on the precision of plant parameters and the noise spectrum. The robustness problem can be formalized in singular value analysis. With the help of ...

The choice of a parameter-passing technique is an important decision in the design of a high-level programming language. To clarify some of the semantic aspects of the decision, we develop, analyze, and compare modifications ...

This thesis presents a systolic algorithm for the SVD of arbitrary complex matrices, based on the cyclic Jacobi method with "parallel ordering". As a basic step in the algorithm, a two-step, two-sided unitary transformation ...

Map-Reduce is a popular distributed programming framework for parallelizing computation on huge datasets over a large number of compute nodes. This year completes a decade since it was invented by Google in 2004. Hadoop, ...