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H∞ state estimation for memristive neural networks with multiple fading measurements., , , , и . Neurocomputing, (2017)Scale Calibration of Deep Ranking Models., , , , и . KDD, стр. 4300-4309. ACM, (2022)Stream-Flow Forecasting Based on Dynamic Spatio-Temporal Attention., , и . IEEE Access, (2019)Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting., , , , , , , , , и 2 other автор(ы). NAACL-HLT (Findings), стр. 1504-1518. Association for Computational Linguistics, (2024)Flow interval prediction based on deep residual network and lower and upper boundary estimation method., , , и . Appl. Soft Comput., (2021)Joint extraction of entities and relations using multi-label tagging and relational alignment., , , , и . Neural Comput. Appl., 34 (8): 6397-6412 (2022)Revisiting Two-tower Models for Unbiased Learning to Rank., , , , , и . SIGIR, стр. 2410-2414. ACM, (2022)Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?, , , , , , , и . ICLR, OpenReview.net, (2021)Towards a Responsive, Yet Power-ef.cient, Operating System: A Holistic Approach., , и . MASCOTS, стр. 249-257. IEEE Computer Society, (2005)Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance., , , , , , , , и . CIKM, стр. 4502-4508. ACM, (2023)