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logistic loss

36 papers

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gradient descent (10) convex optimization (6) generalization bound (5) exponential loss (4) linear classifier (4) convergence rate (4) empirical risk minimization (4) loss function (3) implicit bia (3) convex loss function (3)

Papers

Robust Bi-Tempered Logistic Loss Based on Bregman Divergences NeurIPS 2019 Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate AISTATS 2019 Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss NeurIPS 2018 Linking losses for density ratio and class-probability estimation ICML 2016 On Regularizing Rademacher Observation Losses NeurIPS 2016 Rademacher Observations, Private Data, and Boosting ICML 2015 A Convergence Rate Analysis for LogitBoost, MART and Their Variant ICML 2014 Boosting with the Logistic Loss is Consistent COLT 2013 Margins, Shrinkage, and Boosting ICML 2013 The Fast Convergence of Boosting NeurIPS 2011 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006