We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set...
Grothendieck inequalities are fundamental inequalities which are frequently used in many areas of mathematics and computer science. They can be interpreted as upper bounds for the ...
Constraint satisfaction problems (CSPs) are ubiquitous in many real-world contexts. However, modeling a problem as a CSP can be very challenging, usually requiring considerable ex...
Answering queries over an incomplete database w.r.t. a set of constraints is an important computational task with applications in fields as diverse as information integration and ...
Measuring graph similarity is a key issue in many applications. We propose a new constraint-based modeling language for defining graph similarity measures by means of constraints. ...