Develops O(1)-competitive learning-augmented scheduling algorithms with O(1) preemptions per job for single and unrelated machines, with logarithmic overhead on prediction error, and first such guarantees for unrelated and malleable machines.
We chargeW to the total completion time of these jobs, which increases the competitive ratio by a factor of Θ(1/ν)
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Learning-Augmented Online Scheduling with Parsimonious Preemption
Develops O(1)-competitive learning-augmented scheduling algorithms with O(1) preemptions per job for single and unrelated machines, with logarithmic overhead on prediction error, and first such guarantees for unrelated and malleable machines.