We extend the standard mixture of linear regressions model by allowing mixing proportions to be modeled nonparametrically as a function of the predictors. This framework allows fo...
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Data analytics tools and frameworks abound, yet rapid deployment of analytics solutions that deliver actionable insights from business data remains a challenge. The primary reason...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Mining relational data often boils down to computing clusters, that is finding sub-communities of data elements forming cohesive sub-units, while being well separated from one an...