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We introduce a procedure for conditional density estimation under logarithmic loss, which we call SMP (Sample Minmax Predictor).
Online convex programming and generalized infinitesimal gradient ascent
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Self-concordant analysis for logistic regression
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Learnability, stability and uniform convergence
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Smoothness, low noise and fast rates
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Average stability is invariant to data preconditioning. implications to exp-concave empirical risk minimization
A. Gonen and S. Shalev-Shwartz · 2018
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Finite-sample analysis of M-estimators using self-concordance
D. Ostrovskii and F. Bach · 2018
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