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Found 3 papers, 1 papers with code
Invariance and identifiability issues for word embeddings
Word embeddings are commonly obtained as optimizers of a criterion function $f$ of a text corpus, but assessed on word-task performance using a different evaluation function $g$ of the test data.
Classification and clustering for observations of event time data using non-homogeneous Poisson process models
For clustering, by analogy to the Gaussian mixture model approach for Euclidean data, we consider mixtures of NHPP and use the expectation-maximisation algorithm to estimate the coefficients of the rate functions for the component models and group membership probabilities for each observation.
AMP: a new time-frequency feature extraction method for intermittent time-series data
To demonstrate the effectiveness of AMP, we evaluate against the real word task of clustering intermittent time-series data.
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