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Near-Optimal Algorithms for Private Online Learning in a Stochastic Environment
Specifically, for the problem of decision-theoretic online learning with stochastic rewards, we present the first algorithm that achieves an $ O \left( \frac{ \log K}{ \Delta_{\min}} + \frac{\log(K) \min\{\log (\frac{1}{\Delta_{\min}}), \log(T)\}}{\epsilon} \right)$ regret bound, where $\Delta_{\min}$ is the minimum mean reward gap.
Thompson Sampling for Combinatorial Semi-bandits with Sleeping Arms and Long-Term Fairness Constraints
We study the combinatorial sleeping multi-armed semi-bandit problem with long-term fairness constraints~(CSMAB-F).
Uncertainty measurement with belief entropy on interference effect in Quantum-Like Bayesian Networks
Social dilemmas have been regarded as the essence of evolution game theory, in which the prisoner's dilemma game is the most famous metaphor for the problem of cooperation.
