Data dimensionality estimation methods: a survey

By Francesco Camastra. Pattern Recognition, 2003

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Riemannian Manifold Learning (2008, methodology): “This method, based on nonzero eigenvalues of the covariance matrix, was proposed by Fukunaga and Olsen [38], [39].”
Effect of Non-linear Deep Architecture in Sequence Labeling (2013, background): “Although some studies argue that non-linear neural nets suffer less from the curse of dimensionality (Attali and Pag´es, 1997; Bengio and Bengio, 2000; Pitkow, 2012), counter arguments have been offered (Camastra, 2003; Verleysen et al., 2003).”
Intrinsic dimension estimation: Advances and open problems (2016, background): “Although in the literature there are surveys on ID estimation [12,45], they are dated so that they cannot take into account recent advances in the field.”
Dimensionality of object representations in monkey inferotemporal cortex (2014, methodology): “As described by Camastra (2003), a local method uses only”