نتایج جستجو برای: linear dependencies
تعداد نتایج: 505382 فیلتر نتایج به سال:
A general method is discussed, the-test, which establishes functional dependencies given a table of measurements. The approach is based on calculating conditional probabilities from data densities. Imposing the requirement of continuity of the underlying function the obtained values of the conditional probabilities carry information on the variable dependencies. The power of the method is illus...
In analyzing of modern biological data, we are often dealing with ill-posed problems and missing data, mostly due to high dimensionality and multicollinearity of the dataset. In this paper, we have proposed a system based on matrix factorization (MF) and deep recurrent neural networks (DRNNs) for genotype imputation and phenotype sequences prediction. In order to model the long-term dependencie...
This chapter introduces copula functions and the use of the Gaussian copula function to model probabilistic dependencies in supervised classification tasks. A copula is a distribution function with the implicit capacity to model non linear dependencies via concordance measures, such as Kendall’s τ . Hence, this chapter studies the performance of a simple probabilistic classifier based on the Ga...
We generalize the theory of permutations of names to so-called mutations that transform tuples by introducing duplicates and fresh names. The theory of mutations underpins an algorithm for detecting deadlocks (i.e. circular dependencies between resources) in a model defining dependencies – the language for lams. We demonstrate that our algorithm is a decision procedure for so-called linear lams...
A description of quantitative dependencies by a novel type of fuzzy rules like ‘If X is SMALL then Y is QUICKLY INCREASING’ is considered. The use of such rules for representation of perception based and numerical information about dependencies between variables is discussed. These rules are based on a granulation of directions of function change or slope values. Perception based information gi...
This paper introduces copula functions and the use of the Gaussian copula function to model probabilistic dependencies in supervised classification tasks. A copula is a distribution function with the implicit capacity to model non linear dependencies via concordance measures, such as Kendall’s τ . Hence, this work studies the performance of a simple probabilistic classifier based on the Gaussia...
We present a parser for probabilistic Linear Context-Free Rewriting Systems and use it for constituency and dependency treebank parsing. The choice of LCFRS, a formalism with an extended domain of locality, enables us to model discontinuous constituents and non-projective dependencies in a straightforward way. The parsing results show that, firstly, our parser is efficient enough to be used for...
Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11...
Many studies have shown that selective undo, a variant of the widely-implemented linear undo, has many advantages over the prevailing model. In this paper, we define a task model for implementing selective undo in the face of dependencies that may exist between the undone action and other subsequent user actions. Our model accounts for these dependencies by identifying other actions besides the...
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