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JMLR
2010
143views more  JMLR 2010»
13 years 7 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
IMR
2004
Springer
14 years 2 months ago
A Comparison of Inexact Newton and Coordinate Descent Mesh Optimization Techniques
We compare inexact Newton and coordinate descent methods for optimizing the quality of a mesh by repositioning the vertices, where quality is measured by the harmonic mean of the ...
Lori Freitag Diachin, Patrick M. Knupp, Todd S. Mu...
ICDM
2009
IEEE
152views Data Mining» more  ICDM 2009»
13 years 6 months ago
A Sparsification Approach for Temporal Graphical Model Decomposition
Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct te...
Ning Ruan, Ruoming Jin, Victor E. Lee, Kun Huang
CPHYSICS
2010
184views more  CPHYSICS 2010»
13 years 8 months ago
Parallel Newton-Krylov-Schwarz algorithms for the three-dimensional Poisson-Boltzmann equation in numerical simulation of colloi
We investigate fully parallel Newton-Krylov-Schwarz (NKS) algorithms for solving the large sparse nonlinear systems of equations arising from the finite element discretization of ...
Feng-Nan Hwang, Shang-Rong Cai, Yun-Long Shao, Jon...
MP
2002
84views more  MP 2002»
13 years 8 months ago
A decomposition procedure based on approximate Newton directions
The efficient solution of large-scale linear and nonlinear optimization problems may require exploiting any special structure in them in an efficient manner. We describe and analy...
Antonio J. Conejo, Francisco J. Nogales, Francisco...