Results 71 to 80 of about 40,316 (199)
The role of identification in data‐driven policy iteration: A system theoretic study
International Journal of Robust and Nonlinear Control, EarlyView.Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley +1 more source
Computing Skinning Weights via Convex Duality
Computer Graphics Forum, EarlyView.We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley +1 more source
On the Disentanglement of an Economic Union
Journal of Regional Science, EarlyView.ABSTRACT We study how the unilateral withdrawal of a region from an economic union affects the spatial distribution of economic activity and social welfare. We explore a three‐region economic geography model under the assumption that this withdrawal can be expressed as a higher transportation cost between the leaving party and the remaining union ...
Jorge Saraiva +2 more
wiley +1 more source
Moore-Penrose inverse of a hollow symmetric matrix and a predistance matrix
Special Matrices, 2016 By a hollow symmetric matrix we mean a symmetric matrix with zero diagonal elements. The notion contains those of predistance matrix and Euclidean distance matrix as its special cases.
Kurata Hiroshi, Bapat Ravindra B.
doaj +1 more source
Positive Semidefinite Metric Learning with Boosting
, 2009 The learning of appropriate distance metrics is a critical problem in image classification and retrieval. In this work, we propose a boosting-based technique, termed \BoostMetric, for learning a Mahalanobis distance metric.
Hengel, Anton van den +3 more
core
Markov Determinantal Point Process for Dynamic Random Sets
Journal of Time Series Analysis, EarlyView.ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley +1 more source
Log-Determinant Divergences Revisited: Alpha-Beta and Gamma Log-Det Divergences
Entropy, 2015 This work reviews and extends a family of log-determinant (log-det) divergences for symmetric positive definite (SPD) matrices and discusses their fundamental properties.
Andrzej Cichocki +2 more
doaj +1 more source
Robust Λ$\Lambda$‐Quantiles and Extremal Distributions
Mathematical Finance, EarlyView.ABSTRACT In this paper, we investigate the robust models for Λ$\Lambda$‐quantiles with partial information regarding the loss distribution, where Λ$\Lambda$‐quantiles extend the classical quantiles by replacing the fixed probability level with a probability/loss function Λ$\Lambda$.
Xia Han, Peng Liu
wiley +1 more source
A Geometric Mean of Parameterized Arithmetic and Harmonic Means of Convex Functions
Abstract and Applied Analysis, 2012 The notion of the geometric mean of two positive reals is extended by Ando (1978) to the case of positive semidefinite matrices A and B. Moreover, an interesting generalization of the geometric mean A # B of A and B to convex functions was introduced by ...
Sangho Kum, Yongdo Lim
doaj +1 more source
Hyperbolic Polynomials and Generalized Clifford Algebras [PDF]
, 2012 We consider the problem of realizing hyperbolicity cones as spectrahedra, i.e. as linear slices of cones of positive semidefinite matrices. The generalized Lax conjecture states that this is always possible. We use generalized Clifford algebras for a new
Netzer, Tim, Thom, Andreas
core +1 more source