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The classical perceptron algorithm is an elementary row-action/relaxation algorithm for solving a homogeneous linear inequality system Ax 0. A natural condition measure associated with this algorithm is the Euclidean width T of the cone of feasible solutions, and the iteration complexity of the...
Persistent link: https://www.econbiz.de/10014026694
Persistent link: https://www.econbiz.de/10003745308
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For a conic linear system of the form Ax ∈ K, K a convex cone, several condition measures have been extensively studied in the last dozen years. Among these, Renegar's condition number C(A) is arguably the most prominent for its relation to data perturbation, error bounds, problem geometry,...
Persistent link: https://www.econbiz.de/10014026200
Persistent link: https://www.econbiz.de/10003745309
The classical perceptron algorithm is an elementary row-action/relaxation algorithm for solving a homogeneous linear inequality system Ax 0. A natural condition measure associated with this algorithm is the Euclidean width T of the cone of feasible solutions, and the iteration complexity of the...
Persistent link: https://www.econbiz.de/10005750571
Given a convex body S and a point x in S, let sym(x,S) denote the symmetry value of x in S: sym(x,S):= max{t : x + t(x - y) is in S for every y in S}, which essentially measures how symmetric S is about the point x, and define sym(S):=max{sym(x,S) : x in S}. We call x* a symmetry point of S if...
Persistent link: https://www.econbiz.de/10014029045
We present a general theory for transforming a homogeneous conic system F: Ax = 0, x in C, x non-zero, to an equivalent system via projective transformation induced by the choice of a point in a related dual set. Such a projective transformation serves to pre-condition the conic system into a...
Persistent link: https://www.econbiz.de/10014059687
We develop results for the use of LASSO and Post-LASSO methods to form first-stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p is much larger than the sample size, n. We rigorously develop asymptotic...
Persistent link: https://www.econbiz.de/10014178689
In this chapter we discuss conceptually high dimensional sparse econometric models as well as estimation of these models using ℓ1-penalization and post-ℓ1-penalization methods. Focusing on linear and nonparametric regression frameworks, we discuss various econometric examples, present basic...
Persistent link: https://www.econbiz.de/10014178799