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A joint energy efficiency optimization scheme based on marginal cost and workload prediction in data centers., , , , , , and . Sustain. Comput. Informatics Syst., (2021)A Deep Reinforcement Learning-based Task Scheduling Algorithm for Energy Efficiency in Data Centers., , , , , , , and . ICCCN, page 1-9. IEEE, (2021)Adversarial Attacks to Manipulate Target Localization of Object Detector., , , , , , , and . IEEE Access, (2024)An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction., , , , , and . ISCC, page 1-6. IEEE, (2020)Reinforcement Learning from Human Feedback with Active Queries., , and . Trans. Mach. Learn. Res., (2025)Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers., , , , , , , and . EMNLP (Findings), volume EMNLP 2023 of Findings of ACL, page 13117-13130. Association for Computational Linguistics, (2023)Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models., , , , and . ICML, volume 235 of Proceedings of Machine Learning Research, page 6621-6642. PMLR / OpenReview.net, (2024)P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks., , , , , and . CoRR, (2021)On the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization., , , , and . CoRR, (May 2026)Eco-friendly Dynamic Task Scheduling for Regional Data Center., , , , , and . e-Energy, page 566-571. ACM, (2020)