Solving an integer least squares (ILS) problem usually consists of two stages: reduction and search. This thesis is concerned with the reduction process for the ordinary ILS problem and the ellipsoid-constrained ILS problem. For the ordinary ILS problem, we dispel common misconceptions on the reduction stage in the literature and show what is crucial to the efficiency of the search process. The...

We study the problem of computing the minimum volume enclosing ellipsoid containing a given point set S = {p1, p2, . . . , pn} ⊆ R. Using “core sets” and a column generation approach, we develop a (1 + )-approximation algorithm. We prove the existence of a core set X ⊆ S of size at most |X| = α = O ( d ( log d + 1 )) . We describe an algorithm that computes the set X and a (1 + )-approximation ...

A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able to adapt the distance norm to the underlying distribution of the prototype data poi...

This lecture introduces the Ellipsoid Method, the first polynomialtime algorithm to solve LP. We start by discussing the historical significance of its discovery by L. Khachiyan. Next, we argue that the ability to decide the feasibility of a version of the constraints of an LP is as hard as solving the LP. To gather the intuition behind the Ellipsoid Method, we draw an analogy with a problem of...

In this paper a new iterative approach to probabilistic robust controller design is presented, which is applicable to any robust controller/filter design problem that can be represented as an LMI feasibility problem. Recently, a probabilistic Subgradient Iteration algorithm was proposed for solving LMIs. It transforms the initial feasibility problem to an equivalent convex optimization problem,...

Ellipsoid estimation is important in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and statistical outlier or novelty detection. A new method, called Kernel Minimum Volume Covering Ellipsoid (KMVCE) estimation, that finds an ellipsoid in a kernel-defined feature space is presented. Although the method is v...

In this paper, ellipsoid method for linear programming is derived using only minimal knowledge of algebra and matrices. Unfortunately, most authors first describe the algorithm, then later prove its correctness, which requires a good knowledge of linear algebra.

1. Abstract This paper focuses on the use of minimum norm ellipsoids in stress-based fatigue criteria. We consider both the theoretical issues involved in constructing mathematical models for high cycle fatigue endurance limits and the computational features concerning the application of the resulting fatigue criteria. In the present approach, the macroscopic level of continuum is enhanced with...