A new FTPL algorithm with self-concordant perturbations achieves tilde O(sqrt(T)) regret for all bounded proper losses and O(log T) regret for bounded smooth proper losses in U-calibration.
arXiv preprint arXiv:2501.17205 , year=
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A single algorithm for online multicalibration achieves instance-adaptive rates by dynamically refining a dyadic prediction grid, recovering the worst-case Õ(T^{2/3}) bound and improving to Õ(√T) in marginal stochastic settings and Õ(√(JT)) for J-piecewise stationary means.
Gradient equilibrium is algorithmically equivalent to Blackwell approachability, implying equivalence to regret minimization and calibration.
The book curates and presents proofs of important existing results in conformal prediction in a unified pedagogical format with illustrations.
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Theoretical Foundations of Conformal Prediction
The book curates and presents proofs of important existing results in conformal prediction in a unified pedagogical format with illustrations.