28,737 research outputs found
Feature Selection via Binary Simultaneous Perturbation Stochastic Approximation
Feature selection (FS) has become an indispensable task in dealing with
today's highly complex pattern recognition problems with massive number of
features. In this study, we propose a new wrapper approach for FS based on
binary simultaneous perturbation stochastic approximation (BSPSA). This
pseudo-gradient descent stochastic algorithm starts with an initial feature
vector and moves toward the optimal feature vector via successive iterations.
In each iteration, the current feature vector's individual components are
perturbed simultaneously by random offsets from a qualified probability
distribution. We present computational experiments on datasets with numbers of
features ranging from a few dozens to thousands using three widely-used
classifiers as wrappers: nearest neighbor, decision tree, and linear support
vector machine. We compare our methodology against the full set of features as
well as a binary genetic algorithm and sequential FS methods using
cross-validated classification error rate and AUC as the performance criteria.
Our results indicate that features selected by BSPSA compare favorably to
alternative methods in general and BSPSA can yield superior feature sets for
datasets with tens of thousands of features by examining an extremely small
fraction of the solution space. We are not aware of any other wrapper FS
methods that are computationally feasible with good convergence properties for
such large datasets.Comment: This is the Istanbul Sehir University Technical Report
#SHR-ISE-2016.01. A short version of this report has been accepted for
publication at Pattern Recognition Letter
Automating embedded analysis capabilities and managing software complexity in multiphysics simulation part II: application to partial differential equations
A template-based generic programming approach was presented in a previous
paper that separates the development effort of programming a physical model
from that of computing additional quantities, such as derivatives, needed for
embedded analysis algorithms. In this paper, we describe the implementation
details for using the template-based generic programming approach for
simulation and analysis of partial differential equations (PDEs). We detail
several of the hurdles that we have encountered, and some of the software
infrastructure developed to overcome them. We end with a demonstration where we
present shape optimization and uncertainty quantification results for a 3D PDE
application
The 2005 AMI system for the transcription of speech in meetings
In this paper we describe the 2005 AMI system for the transcription\ud
of speech in meetings used for participation in the 2005 NIST\ud
RT evaluations. The system was designed for participation in the speech\ud
to text part of the evaluations, in particular for transcription of speech\ud
recorded with multiple distant microphones and independent headset\ud
microphones. System performance was tested on both conference room\ud
and lecture style meetings. Although input sources are processed using\ud
different front-ends, the recognition process is based on a unified system\ud
architecture. The system operates in multiple passes and makes use\ud
of state of the art technologies such as discriminative training, vocal\ud
tract length normalisation, heteroscedastic linear discriminant analysis,\ud
speaker adaptation with maximum likelihood linear regression and minimum\ud
word error rate decoding. In this paper we describe the system performance\ud
on the official development and test sets for the NIST RT05s\ud
evaluations. The system was jointly developed in less than 10 months\ud
by a multi-site team and was shown to achieve very competitive performance
Flight experiments using the front-side control technique during piloted approach and landing in a powered lift STOL aircraft
The essential features of using pitch attitude for glidepath control in conjunction with longitudinal thrust modulation for speed control are described, using a simple linearized model for a powered-lift STOL aircraft operating on the backside of the drag curve and at a fixed setting of propulsive lift. It is shown that an automatic speed-hold system incorporating heave-damping augmentation can allow use of the front-side control technique with satisfactory handling qualities, and the results of previous flight investigations are reviewed. Manual control considerations, as they might be involved following failure of the automatic system, are emphasized. The influence of alternative cockpit controller configurations and flight-director display features were assessed for their effect on the control task, which consisted of a straight-in steep approach flown at constant speed in simulated instrument conditions
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