SGD is reformulated via a master equation from discrete updates, producing a discrete Fokker-Planck equation that predicts non-stationary variance growth proportional to learning rate in flat Hessian directions.
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3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Longitudinal evaluation over yearly Android app slices shows temporal drift reduces adversarial robustness of malware detectors, with expanding-window retraining providing partial mitigation but not full recovery.
Hierarchical clustering generates fog colony candidates from device data; NSGA-II selects subsets optimizing network latency and placement runtime across nine scenarios with up to 137 generations needed to dominate controls.
citing papers explorer
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Why SGD is not Brownian Motion: A New Perspective on Stochastic Dynamics
SGD is reformulated via a master equation from discrete updates, producing a discrete Fokker-Planck equation that predicts non-stationary variance growth proportional to learning rate in flat Hessian directions.
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Adversarial Vulnerability Under Temporal Concept Drift: A Longitudinal Study of Android Malware Detection
Longitudinal evaluation over yearly Android app slices shows temporal drift reduces adversarial robustness of malware detectors, with expanding-window retraining providing partial mitigation but not full recovery.
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Genetic-based fog colony optimization hybridized with hierarchical clustering and its influence in the placement of fog services
Hierarchical clustering generates fog colony candidates from device data; NSGA-II selects subsets optimizing network latency and placement runtime across nine scenarios with up to 137 generations needed to dominate controls.