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This paper proposes a bootstrapping conformal prediction approach for constructing prediction intervals to improve right-sizing recommendations for virtual machines in data centers, enhancing cost efficiency and resource allocation.
This paper presents a region-level evaluation framework for EEG-based cognitive workload prediction, showing that frontal electrode groups outperform full-scalp baselines by 15-20% in rank position while using fewer electrodes, supporting efficient workload monitoring systems.