Segmentation is a popular technique for discovering structure in time series data. We address the largely open problem of estimating the number of segments that can be reliably di...
: We conducted psychophysical experiments to gain insight into the semantic categories that guide the human perception of image similarity. We analyzed the perceptual data using mu...
We study the randomized version of a computation model (introduced in [9, 10]) that restricts random access to external memory and internal memory space. Essentially, this model c...
Temporal logics and model-checking have proved successful to respectively express biological properties of complex biochemical systems, and automatically verify their satisfaction...
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...