نتایج جستجو برای: variant kernel prohibits its fast computation especially for large size data unlike time
تعداد نتایج: 12092769 فیلتر نتایج به سال:
abstract birbery and corruption and other criminal and as such is one of social phenomena , and i can firmly say that society is protected and safe from harm , this is criminal . eache community is familiar with these crimes and the crime associated ( direct or indirect ) with the political economic , social , and cultural beliefs and religious issues , especially with the community . admitted...
Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...
Automatic Bayesian Covariance Discovery (ABCD) in Lloyd et al. (2014) provides a framework for automating statistical modelling as well as exploratory data analysis for regression problems. However ABCD does not scale due to its O(N) running time for the kernel search. This is undesirable not only because the average size of data sets is growing fast, but also because there is potentially more ...
writing an academic article requires the researchers to provide support for their works by learning how to cite the works of others. various studies regarding the analysis of citation in m.a theses have been done, while little work has been done on comparison of citations among elt scopus journal articles, and so the dearth of research in this area demands for further investigation into citatio...
The present crisis in global economy, the issue of cli mate change and the fast-growing world population, <span style="font-variant: normal; font-s...
Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pairs of nodes need to be compared. Thus, large parse trees, obtained from HTML documents or structured network data, render convolution kernels inapplicable. In this article, we propose an effective approximation techni...
abstract in first part of this project, the use of a new and biguanid-like catalyst supported on silica as a recyclable catalyst provides a new route for the synthesis of a variety of arylalkylidene rhodanine derivatives through knoevenagle reaction in at present of solvent at room temperature. rhodanine derivatives and especially arylalkylidene rhodanines have proven to be attractive compound...
Squared-loss mutual information (SMI) is a robust measure of the statistical dependence between random variables. The sample-based SMI approximator called least-squares mutual information (LSMI) was demonstrated to be useful in performing various machine learning tasks such as dimension reduction, clustering, and causal inference. The original LSMI approximates the pointwise mutual information ...
Automating statistical modelling is a challenging problem that has far-reaching implications for artificial intelligence. The Automatic Statistician employs a kernel search algorithm to provide a first step in this direction for regression problems. However this does not scale due to its O(N) running time for the model selection. This is undesirable not only because the average size of data set...
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