3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in sequential-quantile-estimation-9
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Use these libraries to find sequential-quantile-estimation-9 models and implementations
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This new algorithm is robust with respect to skewed distributions or ordered datasets and allows separately computed summaries to be combined with no loss in accuracy.
Simulation studies and tests on real data reveal the Gauss-Hermite based algorithms to be competitive with a leading existing algorithm and provide a solution to online distribution function and online quantile function estimation on data streams.
Adding a benchmark result helps the community track progress.