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Exploring Viable Algorithmic Options for Learning from Demonstration (LfD): A Parameterized Complexity Approach
The key to reconciling the polynomial-time intractability of many machine learning tasks in the worst case with the surprising solvability of these tasks by heuristic algorithms in practice seems to be exploiting restrictions on real-world data sets.
Computational Complexity of Segmentation
Computational feasibility is a widespread concern that guides the framing and modeling of biological and artificial intelligence.
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