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Robust unsupervised domain adaptation for neural networks via moment alignment, , , , , and . Information Sciences, (May 2019)On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach, , and . J. Artif. Int. Res., (Feb 11, 2024)On generalization in moment-based domain adaptation, , and . Annals of Mathematics and Artificial Intelligence, 89 (3): 333--369 (Mar 1, 2021)SNN Architecture for Differential Time Encoding Using Decoupled Processing Time, , and . (2023)An optimal $łess$mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si17.svg"$\greater$$łess$mml:mrow$\greater$$łess$mml:mo stretchy="true"$\greater$($łess$/mml:mo$\greater$$łess$mml:mi$\greater$∊$łess$/mml:mi$\greater$$łess$mml:mo$\greater$,$łess$/mml:mo$\greater$$łess$mml:mi$\greater$$\updelta$$łess$/mml:mi$\greater$$łess$mml:mo stretchy="true"$\greater$)$łess$/mml:mo$\greater$$łess$/mml:mrow$\greater$$łess$/mml:math$\greater$-differentially private learning of distributed deep fuzzy models, , , and . Information Sciences, (February 2021)An optimal (∊,δ)-differentially private learning of distributed deep fuzzy models, , , and . Information Sciences, (2021)Rethinking data augmentation for adversarial robustness, , , , , , , and . Information Sciences, (2024)On Leaky-Integrate-and Fire as Spike-Train-Quantization Operator on Dirac-Superimposed Continuous-Time Signals, and . (2024)On generalization in moment-based domain adaptation, , and . Annals of Mathematics and Artificial Intelligence, 89 (3-4): 333--369 (November 2020)On Mitigating the Utility-Loss in Differentially Private Learning: A new Perspective by a Geometrically Inspired Kernel Approach, , and . (2023)cite arxiv:2304.01300.