Process mining offers a way to distill process models from event logs originating from transactional systems in logistics, banking, e-business, health-care, etc. The algorithms us...
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
A common requirement of many scientific applications is the ability to process queries involving expensive predicates corresponding to user programs. Optimizing such queries is ha...
Fabio Porto, Eduardo Sany Laber, Patrick Valduriez
We continue the study of noncommutative polynomial identity testing initiated by Raz and Shpilka and present efficient algorithms for the following problems in the noncommutative...
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...