We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Abstract. In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn featu...
Mustafa Berkay Yilmaz, Hakan Erdogan, Mustafa Unel
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...