Titlebook: Industrial Dynamics and the Evolution of Markets in the Mutual Fund Industry; Andreas Mattig Book 2009 Gabler Verlag | Springer Fachmedien

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Andreas Mattiglity has been proposed as a method to address the problem of bias, giving rise to the popularity of using counterfactuals as a bias mitigation tool. In this paper, we undertake a systematic investigation of the usage of counterfactuals to achieve both statistical and causal-based fairness in facial

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Andreas Mattigction strategy to boost the learning of motion features in video contrastive learning. The proposed method, dubbed .tion-focused .ruple Construction (MoQuad), augments the instance discrimination by meticulously disturbing the appearance and motion of both the positive and negative samples to create

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Andreas Mattigancements further reduce the computational overhead to an affordable level. However, it is still cumbersome to deploy NAS in real-world applications due to the fussy procedures and the supervised learning paradigm. In this work, we propose the self-supervised and weight-preserving neural architectur

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Andreas Mattigrably on well-controlled synthetic datasets, but they do not represent medical imaging contexts. We propose a pipeline that relies on artifacts annotation to enable generalization evaluation and debiasing for the challenging skin lesion analysis context. First, we partition the data into levels of i

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Andreas Mattigspatially consistent dense representation from an image, by randomly sampling and projecting boxes to each augmented view and maximizing the similarity between corresponding box features. We study existing design choices in the literature, such as box generation, feature extraction strategies, and u

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