This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Tradit...
We present the first sound program transformation approach for automatically transforming the code of a legacy web application to employ PREPARE statements in place of unsafe SQL...
Prithvi Bisht, A. Prasad Sistla, V. N. Venkatakris...
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
Abstract Supervised classification is one of the tasks most frequently carried out by socalled Intelligent Systems. Thus, a large number of techniques have been developed based on ...
Sotiris B. Kotsiantis, Ioannis D. Zaharakis, Panay...
The paper presents a clutter detection and removal algorithm for complex document images. The distance transform based approach is independent of clutter's position, size, sh...