Minimal bounds on the mean square error (MSE) are generally used in order to predict the best achievable performance of an estimator for a given observation model. In this paper, w...
Alexandre Renaux, Philippe Forster, Pascal Larzaba...
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
We propose a new model of human concept learning that provides a rational analysis for learning of feature-based concepts. This model is built upon Bayesian inference for a gramma...
Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldma...
Software engineering researchers have long been interested in where and why bugs occur in code, and in predicting where they might turn up next. Historical bug-occurence data has ...
Christian Bird, Adrian Bachmann, Eirik Aune, John ...
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...