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Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment [PDF]
Computer Vision and Pattern Recognition, 2021 Long-tailed data is still a big challenge for deep neural networks, even though they have achieved great success on balanced data. We observe that vanilla training on longtailed data with crossentropy loss makes the instance-rich head classes severely ...
Mengke Li, Yiu‐ming Cheung, Yang Lu
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Mitigating Neural Network Overconfidence with Logit Normalization [PDF]
International Conference on Machine Learning, 2022 Detecting out-of-distribution inputs is critical for safe deployment of machine learning models in the real world. However, neural networks are known to suffer from the overconfidence issue, where they produce abnormally high confidence for both in- and ...
Hongxin Wei +5 more
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Categorical Data Analysis: Away from ANOVAs (transformation or not) and towards Logit Mixed Models.
Journal of Memory and Language, 2008 T. Jaeger, Cognitive Sciences
semanticscholar +3 more sources
Generalized Ordered Logit/Partial Proportional Odds Models for Ordinal Dependent Variables
The Stata Journal, 2006 Richard Williams
semanticscholar +3 more sources
ViM: Out-Of-Distribution with Virtual-logit Matching [PDF]
Computer Vision and Pattern Recognition, 2022 Most of the existing Out-Of-Distribution (OOD) detection algorithms depend on single input source: the feature, the logit, or the softmax probability. However, the immense diversity of the OOD examples makes such methods fragile.
Haoqi Wang +3 more
semanticscholar +1 more source
Computing Interaction Effects and Standard Errors in Logit and Probit Models
The Stata Journal, 2004 E. Norton, Hua Wang, C. Ai
semanticscholar +3 more sources
Logit Margin Matters: Improving Transferable Targeted Adversarial Attack by Logit Calibration [PDF]
IEEE Transactions on Information Forensics and Security, 2023 Previous works have extensively studied the transferability of adversarial samples in untargeted black-box scenarios. However, it still remains challenging to craft targeted adversarial examples with higher transferability than non-targeted ones.
Juanjuan Weng +4 more
semanticscholar +1 more source
Towards Digital Twins of Multimodal Supply Chains
Logistics, 2021 Both modern multi- and intermodal supply chains pose a significant challenge to control and maintain while offering numerous optimization potential. Digital Twins have been proposed to improve supply chains.
Anselm Busse +5 more
doaj +1 more source
Adaptive Logit Adjustment Loss for Long-Tailed Visual Recognition [PDF]
AAAI Conference on Artificial Intelligence, 2021 Data in the real world tends to exhibit a long-tailed label distribution, which poses great challenges for the training of neural networks in visual recognition. Existing methods tackle this problem mainly from the perspective of data quantity, i.e., the
Yan Zhao +4 more
semanticscholar +1 more source