Cause learning from examples--challenges and opportunities

Day - Time: 12 February 2015, h.10:30
Place: Area della Ricerca CNR di Pisa - Room: I-07a
Speakers
  • Junying Zhang (Xidian University, Dept of Computer Science, Xidian, China)
Referent

Ercan Engin Kuruoglu

Abstract

Cause learning from examples is an urgent call and a pathway for understanding the most insights of some scientific problems. A central question is to learn substantial causes which must be a good match to ground truth. Though an anathema is no definition on what to learn: causes, we notice that causes objectively exist, independent to datasets and techniques. The former is a vital clue for learning, while the latter requires that the techniques adopted be hypothesis-free. Learning causes are of great challenges in what to learn, how to learn and how to evaluate what is learnt. The challenges are wonderful opportunities to promote learning from an engineering to a science.

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