Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
- Stable and effective enforcement of hard constraints is one of the crucial components in controlling physics-based dynamic simulation systems. The conventional explicit Baumgarte...
Min Hong, Min-Hyung Choi, Sunhwa Jung, Samuel W. J...
Cooperative problem solving with resource constraints are important in practical multi-agent systems. Resource constraints are necessary to handle practical problems including dis...
Toshihiro Matsui, Hiroshi Matsuo, Marius Silaghi, ...
In this paper we introduce an adaptive technique for compressing small quantities of text which are organized as a rooted directed graph. We impose a constraint on the technique s...