vasospasm
发表于 2025-3-25 06:54:28
René Liechtis performance on unseen data. The phenomenon of the network overfitting the training data, is understood and reported in the literature. Most researchers recommend a ‘trial and error’ approach to selecting the optimal number of weights for the network, which is time consuming, or start with a large
EWER
发表于 2025-3-25 10:45:12
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LARK
发表于 2025-3-25 13:33:47
René Liechti we present a neural network approach for multivariable non-linear kiln process identification and control. Neural networks, in control theory, are attractive because of their powerful capabilities to successfully approximate nonlinear functions within a specified approximation error as recent resea
infinite
发表于 2025-3-25 16:01:34
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ZEST
发表于 2025-3-25 23:52:54
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Insufficient
发表于 2025-3-26 02:41:23
users make sense of algorithmic nudges and how nudges influence users’ views on personalization and attitudes toward news diversity. The findings show that algorithmic nudges play a key role in understanding normative values in NRS, which then influence the user’s intention to consume diverse news.
HEAVY
发表于 2025-3-26 06:16:14
n and whether explainability further moderates this relationship. The findings showed that users with a high heuristic processing of normative values and positive diagnostic perception were more likely to proactively discern misinformation. Users with a high cognitive ability to understand informati
珠宝
发表于 2025-3-26 10:44:27
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Flagging
发表于 2025-3-26 13:01:14
René Liechtiom unintended privacy infringements to solidifying societal biases of gender, race, ethnicity, and culture. The significance of the data used in training algorithms should not be underestimated. Humans should play a part in the datafication of algorithms, as preventing the spread of misinformation i
DAMP
发表于 2025-3-26 16:56:57
René Liechti was a greater drop in algorithmic news when nudging was employed. Moderation from algorithmic trust was found, and users’ trust in algorithmic media amplified the nudge effect only for news from algorithmic media and not nonalgorithmic online media sources. The results of our study confirm previous