Focused on interpreting data as statistical evidence, the evidential paradigm uses likelihood ratios to measure the strength of statistical evidence. Under this paradigm, re-examination of accumulating evidence is encouraged because (i) the likelihood ratio, unlike a p-value, is unaffected by the number of examinations and (ii) the probability of observing strong misleading evidence is naturall...

In many applications of natural language processing it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may need to determine which of the two word combinations \eat a peach" and \eat a beach" is more likely. Statistical NLP methods determine the likelihood of a word combination according to its frequency in a training corpus. However, the n...

Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also play an important role in the presence of constraints on the data distribution. In this paper we present a probabilistic model for “extreme components analysis” (XCA) which at the maximum likelihood solution extracts ...

In many applications of natural language processing it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may need to determine which of the two word combinations “eat a peach” and “eat a beach” is more likely. Statistical NLP methods determine the likelihood of a word combination according to its frequency in a training corpus. However, the n...

College of Liberal Arts, Ludong University, Yantai 264025, China Chinese Lexicography Research Center, Neural Machine Translation (NMT) improves readability by augmenting sentence suggestions based on the precise likelihood words. The word are trained using learning paradigms through repeated translations, searches, and user inputs. However, challenging process is implication NMT for low-resour...

0308-521X/$ see front matter 2010 Elsevier Ltd. doi:10.1016/j.agsy.2010.01.006 * Corresponding author. Tel.: +1 352 392 1864; fax E-mail address: [email protected] (J.W. Jones). Proper estimation of model parameters is required for ensuring accurate model predictions and good model-based decisions. The generalized likelihood uncertainty estimation (GLUE) method is a Bayesian Monte Carlo parameter es...

The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...

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