JMLR
2012
12 years 1 months ago
2012
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
ICASSP
2011
IEEE
13 years 3 months ago
2011
IEEE
This paper considers linear precoding for time-varying multipleinput multiple-output (MIMO) channels. We show that linear minimum mean-squared error (LMMSE) equalization based on ...
INFORMATICALT
1998
13 years 11 months ago
1998
This paper presents a parallel version of a Generalized Conjugate Gradient algorithm proposed by Liu and Story in which the search direction considers the effect of the inexact lin...
IJIT
2004
14 years 27 days ago
2004
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
IJCAI
2007
14 years 28 days ago
2007
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
DAC
2005
ACM
14 years 1 months ago
2005
ACM
This paper proposes a fast decoupling capacitance (decap) allocation and budgeting algorithm for both early stage decap estimation and later stage decap minimization in today’s ...
ARC
2008
Springer
14 years 1 months ago
2008
Springer
As Field Programmable Gate Arrays (FPGAs) have reached capacities beyond millions of equivalent gates, it becomes possible to accelerate floating-point scientific computing applica...
GLOBECOM
2009
IEEE
14 years 2 months ago
2009
IEEE
—This paper discusses the application of iterative versus adaptive equalizers to a Universal Mobile Telecommunications System (UMTS) High Speed Downlink Packet Access (HSDPA) rec...
ICANN
2001
Springer
14 years 4 months ago
2001
Springer
The method of conjugate gradients provides a very effective way to optimize large, deterministic systems by gradient descent. In its standard form, however, it is not amenable to ...