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GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
13 years 7 months ago
Parsimonious regularization using genetic algorithms applied to the analysis of analytical ultracentrifugation experiments
Frequently in the physical sciences experimental data are analyzed to determine model parameters using techniques known as parameter estimation. Eliminating the effects of noise ...
Emre H. Brookes, Borries Demeler
ICASSP
2010
IEEE
13 years 4 months ago
Optimization of a maximum entropy criterion for 2D Nuclear Magnetic Resonance reconstruction
This paper deals with the reconstruction of T1-T2 correlation spectra in Nuclear Magnetic Resonance (NMR) spectroscopy. The ill-posed character of this inverse problem and its lar...
Emilie Chouzenoux, Saïd Moussaoui, Jér...
NIPS
2008
13 years 7 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
ICML
2005
IEEE
14 years 6 months ago
The cross entropy method for classification
We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...
Shie Mannor, Dori Peleg, Reuven Y. Rubinstein
ISAMI
2010
13 years 3 months ago
Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their Entropy
Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
Sérgio A. D. Deusdado, Paulo Carvalho