For ambiguous objects which have multiple semantic meanings, traditional machine learning frameworks may be less powerful. This talk will introduce a new ...
Why MIML ? MIML captures more information of ambiguous data. Appropriate representation is important. Having an appropriate representation is as important ...
For ambiguous objects which have multiple semantic meanings, traditional machine learning frameworks may be less powerful. This talk will introduce a new ...
This talk will introduce a new framework for machine learning with ambiguous objects, which aims to improve the performance of the system automatically by ...
Machine learning tries to improve the performance of the system automatically by learning from experiences, e.g., objects or events given to the system as ...
Comparing with traditional learning frameworks, the MIML framework is more convenient and natural for representing ambiguous objects. To learn MIML examples, we ...
presents a statistical learning theoretic framework for learning from ambiguous examples that is based on a novel formalization of disambiguation ...
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Dec 15, 2022 · We introduce CLAM: a framework for getting language models to selectively ask for clarification about ambiguous user questions.
Oct 23, 2024 · In this study, a method for uniquely detecting the ambiguous contours of a debris cloud based on supervised machine learning and a continuous wavelet transform ...
Mar 14, 2024 · Each video shows morphing ambiguous imagery that at times vaguely resembles things like landscapes or airplanes, but often escapes clear ...