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136
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ICANN
2009
Springer
15 years 8 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
ICCS
2003
Springer
15 years 9 months ago
Monte Carlo Method for Calculating the Electrostatic Energy of a Molecule
The problem of computing the electrostatic energy of a large molecule is considered. It is reduced to solving the Poisson equation inside and the linear Poisson-Boltzmann equation ...
Michael Mascagni, Nikolai A. Simonov
155
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ICML
2009
IEEE
16 years 4 months ago
A least squares formulation for a class of generalized eigenvalue problems in machine learning
Many machine learning algorithms can be formulated as a generalized eigenvalue problem. One major limitation of such formulation is that the generalized eigenvalue problem is comp...
Liang Sun, Shuiwang Ji, Jieping Ye
134
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ICASSP
2010
IEEE
15 years 3 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
128
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HYBRID
2010
Springer
15 years 10 months ago
Automatic invariant generation for hybrid systems using ideal fixed points
We present computational techniques for automatically generating algebraic (polynomial equality) invariants for algebraic hybrid systems. Such systems involve ordinary differentia...
Sriram Sankaranarayanan