In this paper, we consider a decision-maker who tries to learn the distribution of outcomes from previously observed cases. For each observed database of cases the decision-maker ...
We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by Score Matching, a recently proposed est...
We introduce into the classical Perceptron algorithm with margin a mechanism of unlearning which in the course of the regular update allows for a reduction of possible contributio...
This work presents the concept of Continuous Search (CS), which objective is to allow any user to eventually get their constraint solver achieving a top performance on their proble...
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...