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» Using Gaussian Processes to Optimize Expensive Functions
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JMLR
2012
11 years 10 months ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
ICML
2007
IEEE
14 years 8 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
IC3
2010
13 years 7 months ago
LACAIS: Learning Automata Based Cooperative Artificial Immune System for Function Optimization
Artificial Immune System (AIS) is taken into account from evolutionary algorithms that have been inspired from defensive mechanism of complex natural immune system. For using this ...
Alireza Rezvanian, Mohammad Reza Meybodi
NAACL
2003
13 years 9 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
PAMI
2011
13 years 2 months ago
Approximately Global Optimization for Robust Alignment of Generalized Shapes
—In this paper, we introduce a novel method to solve shape alignment problems. We use gray-scale “images” to represent source shapes, and propose a novel two-component Gaussi...
Hongsheng Li, Tian Shen, Xiaolei Huang