Testing Semantic Importance via Betting
–Neural Information Processing Systems
Providing guarantees on the decision-making processes of autonomous systems, often based on complex black-box machine learning models, is paramount for their safe deployment. This need motivates efforts towards responsible artificial intelligence, which broadly entails questions of reliability, robustness, fairness, and interpretability.
Neural Information Processing Systems
Feb-16-2026, 12:34:08 GMT
- Country:
- Asia
- Japan > Honshū
- Kantō > Kanagawa Prefecture (0.04)
- Middle East > Jordan (0.04)
- Japan > Honshū
- Europe
- Switzerland > Zürich
- Zürich (0.14)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- Switzerland > Zürich
- Asia
- Genre:
- Overview (0.67)
- Research Report
- Experimental Study (1.00)
- New Finding (0.67)
- Industry:
- Health & Medicine (0.67)
- Transportation > Air (0.34)
- Technology:
- Information Technology > Artificial Intelligence
- Issues > Social & Ethical Issues (0.68)
- Machine Learning
- Performance Analysis > Accuracy (0.93)
- Statistical Learning (1.00)
- Natural Language (1.00)
- Representation & Reasoning (1.00)
- Vision (1.00)
- Information Technology > Artificial Intelligence