We consider the stochastic Steiner forest problem: suppose we were given a collection of Steiner forest instances, and were guaranteed that a random one of these instances would a...
The low-rank matrix approximation problem involves finding of a rank k version of a m ? n matrix AAA, labeled AAAk, such that AAAk is as "close" as possible to the best ...
Blocks is an open source modular MATLAB framework which allows the user to avoid needlessly repeating computation.
Blocks may be easily used for your own experiments, and comes ...
I am a Ph.D. student working with Chuck Anderson studying reinforcement learning. I also enjoy high dimensional data issues, mixture models, neural networks, and simple, yet effec...
Abstract. Many combinatorial problems encountered in practice involve constraints that require that a set of variables take distinct or equal values. The AllDifferent constraint, i...
Decision tree induction techniques attempt to find small trees that fit a training set of data. This preference for smaller trees, which provides a learning bias, is often justifie...
Christian Bessiere, Emmanuel Hebrard, Barry O'Sull...
We investigate soft open constraints. We generalize and unify classes of soft constraints and adapt them to the open setting. We give sufficient conditions for generalized classes ...
This paper deals with the challenging problem of counting the number of solutions of a CSP, denoted #CSP. Recent progress have been made using search methods, such as BTD [15], whi...
Abstract. This paper introduces a generalization of the nvalue constraint that bounds the number of distinct values taken by a set of variables.The generalized constraint (called n...