Saman Vaisipour

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Gene expression microarrays are widely used to better understand the complex biological mechanisms inside cells. One of the main obstacles of applying statistical learning algorithms to microarray data is the large gap between the number of features (p) and the number of available instances (n), i.e., the “large p, small n” challenge. This thesis explores(More)
Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65 ♀) in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n(More)
In this paper a method for detecting out of vocabulary words in isolated word recognizers is introduced, our method utilized new kinds of confidence measure. After recognition task was completed and consequently confidence measure was extracted, a classifier would accept or reject result of recognition task using this CM.We used two different kinds of(More)
A comprehensive speech database is one of the important tools for developing speech recognition systems; these tools are necessary for telephony recognition, too. Although adequate databases for direct speech recognizers exist, there is not an appropriate database for telephony speech recognizers. Most methods suggested for solving this problem are based on(More)
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