Results 1  10
of
2,390
Penalty ∫ Term
"... Given a time series of observed positions {ri} N i=0 objective is to generate a smooth trajectory to fit these data points. in three dimensional space, our primary A penalty term is introduced to assure smoothness of the reconstructed trajectory. N∑ ‖r(ti) − ri ‖ 2 ..."
Abstract
 Add to MetaCart
Given a time series of observed positions {ri} N i=0 objective is to generate a smooth trajectory to fit these data points. in three dimensional space, our primary A penalty term is introduced to assure smoothness of the reconstructed trajectory. N∑ ‖r(ti) − ri ‖ 2
Representation of the penalty term of dynamic concave utilities
, 2008
"... In the context of a Brownian filtration and with a fixed finite time horizon, we will provide a representation of the penalty term of general dynamic concave utilities (hence of dynamic convex risk measures) by applying the theory of gexpectations. 1 ..."
Abstract

Cited by 32 (2 self)
 Add to MetaCart
In the context of a Brownian filtration and with a fixed finite time horizon, we will provide a representation of the penalty term of general dynamic concave utilities (hence of dynamic convex risk measures) by applying the theory of gexpectations. 1
Secondorder Learning Algorithm with Squared Penalty Term
"... This paper compares three penalty terms with respect to the efficiency of supervised learning, by using first and secondorder learning algorithms. Our experiments showed that for a reasonably adequate penalty factor, the combination of the squared penalty term and the secondorder learning algorit ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
This paper compares three penalty terms with respect to the efficiency of supervised learning, by using first and secondorder learning algorithms. Our experiments showed that for a reasonably adequate penalty factor, the combination of the squared penalty term and the secondorder learning
Evaluation of a Rigidity Penalty Term for Nonrigid Registration
"... Nonrigid registration of medical images usually does not model properties of different tissue types. This results for example in nonrigid deformations of structures that are rigid. In this work we address this problem by employing a local rigidity penalty term. We illustrate this approach on a 2D s ..."
Abstract
 Add to MetaCart
Nonrigid registration of medical images usually does not model properties of different tissue types. This results for example in nonrigid deformations of structures that are rigid. In this work we address this problem by employing a local rigidity penalty term. We illustrate this approach on a 2D
Robust utility maximization with an entropic penalty term: Stochastic control and BSDE methods
, 2005
"... Robust utility maximization with an entropic penalty term: Stochastic control and BSDE methods ..."
Abstract
 Add to MetaCart
Robust utility maximization with an entropic penalty term: Stochastic control and BSDE methods
Sparse regularization with l q penalty term
 Inverse Probl
, 2008
"... We consider the stable approximation of sparse solutions to nonlinear operator equations by means of Tikhonov regularization with a subquadratic penalty term. Imposing certain assumptions, which for a linear operator are equivalent to the standard range condition, we derive the usual convergence ra ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
We consider the stable approximation of sparse solutions to nonlinear operator equations by means of Tikhonov regularization with a subquadratic penalty term. Imposing certain assumptions, which for a linear operator are equivalent to the standard range condition, we derive the usual convergence
An Optimal Preconditioner for a Class of Saddle Point Problems with a Penalty Term
 SIAM J. Sci. Comput
, 1995
"... . Iterative methods are considered for a class of saddle point problems with a penalty term arising from finite element discretizations of certain elliptic problems. An optimal preconditioner which is independent of the discretization and the penalty parameter is constructed. This approach is then u ..."
Abstract

Cited by 43 (4 self)
 Add to MetaCart
. Iterative methods are considered for a class of saddle point problems with a penalty term arising from finite element discretizations of certain elliptic problems. An optimal preconditioner which is independent of the discretization and the penalty parameter is constructed. This approach
Model Selection for Sinusoids in Noise: Statistical Analysis and a New Penalty Term
"... Abstract—Detection of the number of sinusoids embedded in noise is a fundamental problem in statistical signal processing. Most parametric methods minimize the sum of a data fit (likelihood) term and a complexity penalty term. The latter is often derived via information theoretic criteria, such as m ..."
Abstract

Cited by 6 (0 self)
 Add to MetaCart
Abstract—Detection of the number of sinusoids embedded in noise is a fundamental problem in statistical signal processing. Most parametric methods minimize the sum of a data fit (likelihood) term and a complexity penalty term. The latter is often derived via information theoretic criteria
Use of penalty terms in gradientbased iterative reconstruction schemes for optical tomography
 J. Biomed. Opt
"... Abstract. It is well known that the reconstruction problem in optical tomography is illposed. In other words, many different spatial distributions of optical properties inside the medium can lead to the same detector readings on the surface of the medium under consideration. Therefore, the choice ..."
Abstract

Cited by 12 (3 self)
 Add to MetaCart
of an appropriately defined objective function. The objective function can be separated into a leastsquareerror term, which compares predicted and actual detector readings, and additional penalty terms that may contain a priori information about the system. For the efficient minimization of this objective function
Results 1  10
of
2,390