Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
We describe a cognitive architecture for creating more robust intelligent systems by executing hybrids of algorithms based on different computational formalisms. The architecture ...
Nicholas L. Cassimatis, Perrin G. Bignoli, Magdale...
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
Over the past decade, the advancement of a myriad of methods, techniques and technologies to conceal digital evidence and covertly communicate have increased at an alarming rate. I...
We consider the problem of efficiently sampling Web search engine query results. In turn, using a small random sample instead of the full set of results leads to efficient approxi...
Aris Anagnostopoulos, Andrei Z. Broder, David Carm...