cross entropy
PulseAugur coverage of cross entropy — every cluster mentioning cross entropy across labs, papers, and developer communities, ranked by signal.
1 天有情绪数据
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New losses achieve Neural Collapse faster in supervised learning
Researchers have introduced new methods, NTCE and NONL, to improve supervised classification by achieving Neural Collapse (NC) more efficiently. These techniques address limitations in existing paradigms like cross-entr…
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Researchers develop Evolutionary Dynamic Loss for distribution-free pretraining
Researchers have developed a new framework called Evolutionary Dynamic Loss (EDL) for pretraining classification losses. EDL learns a transferable loss function using synthetic data, avoiding the need for real samples d…
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Linear-Core Surrogates offer smooth loss functions with linear rates for classification
Researchers have introduced Linear-Core (LC) Surrogates, a novel family of convex loss functions designed to combine the benefits of smooth and piecewise-linear losses in machine learning. These surrogates are different…
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Contrastive learning advances model robustness and transparency in AI
Contrastive learning is a machine learning technique that creates an embedding space where similar data points are grouped together and dissimilar ones are separated. This method can be applied in both supervised and un…