We consider the problem of learning sparse parities in the presence of noise. For learning parities on r out of n variables, we give an algorithm that runs in time poly log 1 δ , ...
We describe a reduction from the problem of unordered search (with a unique solution) to the problem of inverting a permutation. Since there is a straightforward reduction in the ...
—The Support Vector Machine is a widely employed machine learning model due to its repeatedly demonstrated superior generalization performance. The Sequential Minimal Optimizatio...
Christopher Sentelle, Michael Georgiopoulos, Georg...
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
The Pfair algorithms are optimal for independent periodic real-time tasks executing on a multiple-resource system, however, they incur a high scheduling overhead by making schedul...