Incremental and Adaptive Machine Learning KU Leuven
As humans we learn continually throughout our lifetime, we are adaptive to ever-changing environments, and can exploit obtained knowledge to swiftly pick up novel or more advanced concepts. This is in stark contrast to the standard machine learning paradigm, where learning a model occurs strictly once before using its knowledge in practice. Limitations arise from a static model, as our world is ever-changing, pushing the need for a more ...