Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
Discovering interesting patterns from high-speed data streams is a challenging problem in data mining. Recently, the support metric-based frequent pattern mining from data stream h...
In this paper, we ask if the traditional relational query acceleration techniques of summary tables and covering indexes have analogs for branching path expression queries over tr...
Raghav Kaushik, Philip Bohannon, Jeffrey F. Naught...
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
We present the design and development of a Visual Learning Engine, a tool that can form the basis for interactive development of visually rich teaching and learning modules across...