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LeastSquares Policy Iteration
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2003
"... We propose a new approach to reinforcement learning for control problems which combines valuefunction approximation with linear architectures and approximate policy iteration. This new approach ..."
Abstract

Cited by 461 (12 self)
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We propose a new approach to reinforcement learning for control problems which combines valuefunction approximation with linear architectures and approximate policy iteration. This new approach
Least Median of Squares Regression
 JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
, 1984
"... ..."
A leastsquares finite element method for the NavierStokes equations
 Appl. Math. Lett
, 1993
"... Abstract. In this paper we study finite element methods of leastsquares type for the stationary, incompressible NavierStokes equations in 2 and 3 dimensions. We consider methods based on velocityvorticitypressure form of the NavierStokes equations augmented with several nonstandard boundary con ..."
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Cited by 63 (17 self)
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Abstract. In this paper we study finite element methods of leastsquares type for the stationary, incompressible NavierStokes equations in 2 and 3 dimensions. We consider methods based on velocityvorticitypressure form of the NavierStokes equations augmented with several nonstandard boundary
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
 ACM Trans. Math. Software
, 1982
"... An iterative method is given for solving Ax ~ffi b and minU Ax b 112, where the matrix A is large and sparse. The method is based on the bidiagonalization procedure of Golub and Kahan. It is analytically equivalent to the standard method of conjugate gradients, but possesses more favorable numerica ..."
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Cited by 649 (21 self)
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gradient algorithms, indicating that I~QR is the most reliable algorithm when A is illconditioned. Categories and Subject Descriptors: G.1.2 [Numerical Analysis]: ApprorJmationleast squares approximation; G.1.3 [Numerical Analysis]: Numerical Linear Algebralinear systems (direct and
Mass and momentum conservation of the LeastSquares Spectral Collocation Method for the NavierStokes
"... equations ..."
Negative norm leastsquares methods for the velocityvorticitypressure NavierStokes equations
 Numerical Methods in PDE’s
, 1999
"... We develop and analyze a leastsquares finite element method for the steady state, incompressible NavierStokes equations, written as a firstorder system involving vorticity as new dependent variable. In contrast to standard L 2 leastsquares methods for this system, our approach utilizes discrete ..."
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Cited by 6 (5 self)
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We develop and analyze a leastsquares finite element method for the steady state, incompressible NavierStokes equations, written as a firstorder system involving vorticity as new dependent variable. In contrast to standard L 2 leastsquares methods for this system, our approach utilizes discrete
ENHANCED MASS CONSERVATION IN LEASTSQUARES METHODS FOR NAVIERSTOKES EQUATIONS∗
"... Abstract. There are many applications of the leastsquares finite element method for the numerical solution of partial differential equations because of a number of benefits that the leastsquares method has. However, one of most wellknown drawbacks of the leastsquares finite element method is the ..."
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Cited by 5 (1 self)
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is the lack of exact discrete mass conservation, in some contexts, due to the fact that leastsquares method minimizes the continuity equation in L2 norm. In this paper, we explore the reason of the mass loss and provide new approaches to retain the mass even in severely underresolved grid. Key words. NavierStokes
Experiences with negative norm leastsquares methods for the NavierStokes equations
 ETNA
, 1997
"... Abstract. This paper is concerned with the implementation and numerical study of a discrete negative norm leastsquares method for the NavierStokes equations proposed in [2] and [3]. The main focus of the paper is on the algorithmic development and computational analysis of this method, including d ..."
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Cited by 4 (3 self)
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Abstract. This paper is concerned with the implementation and numerical study of a discrete negative norm leastsquares method for the NavierStokes equations proposed in [2] and [3]. The main focus of the paper is on the algorithmic development and computational analysis of this method, including
LeastSquares Method
, 2009
"... A highorder Galerkin LeastSquares (GLS) finite element discretization is combined with massively parallel implicit solvers. The stabilization parameter of the GLS discretization is modified to improve the resolution characteristics and the condition number for the highorder interpolation. The Bal ..."
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A highorder Galerkin LeastSquares (GLS) finite element discretization is combined with massively parallel implicit solvers. The stabilization parameter of the GLS discretization is modified to improve the resolution characteristics and the condition number for the highorder interpolation
Benchmarking Least Squares Support Vector Machine Classifiers
 NEURAL PROCESSING LETTERS
, 2001
"... In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LSSVMs), a least squares cost function is proposed so as to obtain a linear set of eq ..."
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Cited by 446 (46 self)
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In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LSSVMs), a least squares cost function is proposed so as to obtain a linear set
Results 1  10
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793,253