Tag: binary
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Robust low-rank estimation with multiple binary responses using pairwise AUC loss
Robust low-rank estimation with multiple binary responses using pairwise AUC loss arXiv:2601.08618v1 Announce Type: new Abstract: Multiple binary responses arise in many modern data-analytic problems. Although fitting separate logistic regressions for each response is computationally attractive, it ignores shared structure and can be statistically inefficient, especially in high-dimensional and class-imbalanced regimes. Low-rank models offer a…
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When Less Is More: Binary Feedback Can Outperform Ordinal Comparisons in Ranking Recovery
When Less Is More: Binary Feedback Can Outperform Ordinal Comparisons in Ranking Recovery arXiv:2507.01613v1 Announce Type: new Abstract: Paired comparison data, where users evaluate items in pairs, play a central role in ranking and preference learning tasks. While ordinal comparison data intuitively offer richer information than binary comparisons, this paper challenges that conventional wisdom. We…
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Class-Balance Bias in Regularized Regression
Class-Balance Bias in Regularized Regression arXiv:2501.03821v1 Announce Type: new Abstract: Regularized models are often sensitive to the scales of the features in the data and it has therefore become standard practice to normalize (center and scale) the features before fitting the model. But there are many different ways to normalize the features and the choice…