The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e. the ...
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...