Bridging belief function theory to modern machine learning
arXiv:1504.03874v1
Originality Synthesis-oriented
AI Analysis
It suggests a potential shift for machine learning practitioners, but is incremental as it builds on existing belief function theory without demonstrated impact.
The paper proposes exploring new trends in modern machine learning, arguing that the belief function framework can play a major role in addressing its evolving questions, but provides no concrete results or numbers.
Machine learning is a quickly evolving field which now looks really different from what it was 15 years ago, when classification and clustering were major issues. This document proposes several trends to explore the new questions of modern machine learning, with the strong afterthought that the belief function framework has a major role to play.