HiePaCo: Scalable Hierarchical Exploration in Abstract Parallel Coordinates Under Budget Constraints

Exploring Hierarchical Rule Systems in Parallel Coordinates

Rule systems have failed to attract much interest in large data analysis problems because they tend to be too simplistic to be useful or consist of too many rules for human interpretation. We recently presented a method that constructs a hierarchical rule system, with only a small number of rules at each level of the hierarchy. Lower levels in this hierarchy focus on outliers or areas of the fe...

Supervised Sequential Classification Under Budget Constraints

In this paper we develop a framework for a sequential decision making under budget constraints for multi-class classification. In many classification systems, such as medical diagnosis and homeland security, sequential decisions are often warranted. For each instance, a sensor is first chosen for acquiring measurements and then based on the available information one decides (rejects) to seek mo...

Crowdsourcing Complex Workflows under Budget Constraints

We consider the problem of task allocation in crowdsourcing systems with multiple complex workflows, each of which consists of a set of inter-dependent micro-tasks. We propose Budgeteer, an algorithm to solve this problem under a budget constraint. In particular, our algorithm first calculates an efficient way to allocate budget to each workflow. It then determines the number of inter-dependent...

Selecting a Response Plan Under Budget Constraints

Very Fast Kernel SVM under Budget Constraints

In this paper we propose a fast online Kernel SVM algorithm under tight budget constraints. We propose to split the input space using LVQ and train a Kernel SVM in each cluster. To allow for online training, we propose to limit the size of the support vector set of each cluster using different strategies. We show in the experiment that our algorithm is able to achieve high accuracy while having...