In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...
Spectral methods for nonlinear dimensionality reduction (NLDR) impose a neighborhood graph on point data and compute eigenfunctions of a quadratic form generated from the graph. W...
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem b...