Human visual capability has remained largely beyond the reach of engineered systems despite intensive study and considerable progress in problem understanding, algorithms and comp...
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
Kernel Miner is a new data-mining tool based on building the optimal decision forest. The tool won second place in the KDD'99 Classifier Learning Contest, August 1999. We des...
- In this paper we propose a new methodology for Cost-Benefit analysis in a multiple time series prediction problem. The proposed model is evaluated in a real world application bas...
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...