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Found 7 papers, 0 papers with code
Learnability is a Compact Property
Furthermore, the learnability of such problems can fail to be a property of finite character: informally, it cannot be detected by examining finite projections of the problem.
Regularization and Optimal Multiclass Learning
We demonstrate that an agnostic version of the Hall complexity again characterizes error rates exactly, and exhibit an optimal learner using maximum entropy programs.
On the Distortion of Voting with Multiple Representative Candidates
Our main result is a clean and tight characterization of positional voting rules that have constant expected distortion (independent of the number of candidates and the metric space).
Of the People: Voting Is More Effective with Representative Candidates
However, we show that independence alone is not enough to achieve the upper bound: even when candidates are drawn independently, if the population of candidates can be different from the voters, then an upper bound of $2$ on the approximation is tight.
Mitigating the Curse of Correlation in Security Games by Entropy Maximization
To mitigate this issue, we propose to design entropy-maximizing defending strategies for spatio-temporal security games, which frequently suffer from CoC.
Security Games with Information Leakage: Modeling and Computation
Our experiments confirm the necessity of handling information leakage and the advantage of our algorithms.
Dynamic Pricing with Limited Supply
The performance guarantee for the same mechanism can be improved to $O(\sqrt{k} \log n)$, with a distribution-dependent constant, if $k/n$ is sufficiently small.
