CORDIS Project
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This research focuses on improving machine learning performance using large-scale, low-quality datasets. It aims to develop methods for learning deep data representations and optimizing decision-making under uncertainty, addressing challenges in areas like computer vision and natural language processing.
Machine learning was born in an era when most datasets were small, low-dimensional, and used carefully hand-crafted features.
However, recent years have seen a dramatic change in the nature of typical machine learning tasks:
These are now routinely performed on huge, web-scale datasets, with data quantity no longer being a major bottleneck.
On the flip side, the large-scale and automated data-gathering methods used to create such massive datasets often go hand-in-hand with mediocre quality of in…
WEIZMANN INSTITUTE OF SCIENCE
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