diffRL enables verification of symbolic properties over input ranges for DRL agents in adaptive video streaming, wireless resource management, and congestion control by decomposing them into tractable sub-properties for existing DNN verifiers.
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SANJESH applies bi-level optimization to production traces and reveals VM allocation scenarios that cause 4x worse performance than the operator's existing evaluator detected.
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Analyzing Symbolic Properties for DRL Agents in Systems and Networking
diffRL enables verification of symbolic properties over input ranges for DRL agents in adaptive video streaming, wireless resource management, and congestion control by decomposing them into tractable sub-properties for existing DNN verifiers.
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A Performance Analyzer for a Public Cloud's ML-Augmented VM Allocator
SANJESH applies bi-level optimization to production traces and reveals VM allocation scenarios that cause 4x worse performance than the operator's existing evaluator detected.