The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
The increasing complexity of hardware features for recent processors makes high performance code generation very challenging. In particular, several optimization targets have to b...
We present a flexible new optimization framework for finding effective, reliable pseudo-relevance feedback models that unifies existing complementary approaches in a principled wa...
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...
This paper describes a method to use compiled, strongly typed Aldor domains in the interpreted, expression-oriented Maple environment. This represents a non-traditional approach t...