Derives generalization bounds for quantum learning via quantum and classical Rényi divergences, with a new modified sandwich quantum Rényi divergence shown to outperform the Petz version analytically and numerically.
On the uniform convergence of relative frequencies of events to their probabilities
2 Pith papers cite this work. Polarity classification is still indexing.
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Prospective Learning with Control proves ERM asymptotically achieves the Bayes optimal policy in non-stationary reset-free settings and outperforms time-aware RL on a 1D foraging benchmark.
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Generalization Bounds for Quantum Learning via R\'enyi Divergences
Derives generalization bounds for quantum learning via quantum and classical Rényi divergences, with a new modified sandwich quantum Rényi divergence shown to outperform the Petz version analytically and numerically.
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Optimal control of the future via prospective learning with control
Prospective Learning with Control proves ERM asymptotically achieves the Bayes optimal policy in non-stationary reset-free settings and outperforms time-aware RL on a 1D foraging benchmark.