One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
Ajay J. Joshi, Fatih Porikli, Nikolaos Papanikolop...
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
Log preprocessing, a process applied on the raw log before applying a predictive method, is of paramount importance to failure prediction and diagnosis. While existing filtering ...
Ziming Zheng, Zhiling Lan, Byung-Hoon Park, Al Gei...
We consider the problem of querying data sources that have limited capabilities and can thus only be accessed by complying with certain binding patterns for their attributes. This ...
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...