A PPO-based autoscaler for GPU inference in Kubernetes is claimed to cut P95 latency up to 6.7x, but the evidence is weakened by a missing HPA baseline, a spike-traffic slowdown, and a reliance on synthetic feedback.
Cross- view feature learning via structures unlocking based on robust low-rank constraint,
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KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling
A PPO-based autoscaler for GPU inference in Kubernetes is claimed to cut P95 latency up to 6.7x, but the evidence is weakened by a missing HPA baseline, a spike-traffic slowdown, and a reliance on synthetic feedback.