In Reinforcement Learning (RL) environments, detecting environment drift is essential for maintaining robust policy performance in production systems, particularly within the context of MLOps. This paper proposes EDSVM, a novel environment drift detection method, which trains Support Vector Machines on undrifted and synthetic drifted examples generated
Zhizhou Fang, Uwe Zdun
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Design and Validation of a Discipline-Oriented Curriculum Model for Elementary Education with an Emphasis on Gardner\'s Five Minds Approach [PDF]
Objective: The aim of this research was to design and validate a discipline-oriented curriculum model for elementary education with an emphasis on Gardner's Five Minds approach. Methods: This study employed a mixed exploratory sequential research method.
Mehzad Alirezaei +2 more
doaj
Protocol to benchmark and evaluate the status of imbalance measure using correlation, data complexity, and ablation analyses. [PDF]
Pivin-Bachler JR, van den Broek EL.
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Deep Learning-Based Automatic Modulation Classification for OFDM Signals: From Synthetic Training to OTA Evaluation. [PDF]
Nelega R +4 more
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HybridTrust: on-device federated learning with crypto-agile security for legacy and quantum-safe medical devices. [PDF]
Khan UH +5 more
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Interrogating the synthetic likelihood of metal-organic frameworks: a digital discovery perspective. [PDF]
Wu X, Jiang J.
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Linking Synthetic Materials Chemistry to Electrocatalytic Performance. [PDF]
Bagchi D +3 more
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Inferring genotype-phenotype maps using attention models. [PDF]
Rijal K +5 more
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Machine Learning-Based Pitting Rate Classification and Prediction for 316L Stainless Steel in NaClO<sub>3</sub> and NaCl Environment. [PDF]
Zhang C, Yao J, Zhang Z.
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Generative artificial intelligence in animal genomics for smart agriculture: Applications, challenges, and future prospects. [PDF]
Ghavi Hossein-Zadeh N.
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