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Found 3 papers, 1 papers with code
Conformal Prediction via Regression-as-Classification
Conformal prediction (CP) for regression can be challenging, especially when the output distribution is heteroscedastic, multimodal, or skewed.
On the Diminishing Returns of Width for Continual Learning
While deep neural networks have demonstrated groundbreaking performance in various settings, these models often suffer from \emph{catastrophic forgetting} when trained on new tasks in sequence.
On Accelerated Perceptrons and Beyond
The classical Perceptron algorithm of Rosenblatt can be used to find a linear threshold function to correctly classify $n$ linearly separable data points, assuming the classes are separated by some margin $\gamma > 0$.
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