Results 11 to 20 of about 103,215 (258)
Generalized score matching for general domains [PDF]
Information and Inference: A Journal of the IMA, 2021 Abstract Estimation of density functions supported on general domains arises when the data are naturally restricted to a proper subset of the real space. This problem is complicated by typically intractable normalizing constants. Score matching provides a powerful tool for estimating densities with such intractable normalizing constants ...
Yu, Shiqing +2 more
openaire +3 more sources
Inter-domain curriculum learning for domain generalization
ICT Express, 2022 Domain generalization aims to learn a domain-invariant representation from multiple source domains so that a model can generalize well across unseen target domains.
Daehee Kim, Jinkyu Kim, Jaekoo Lee
doaj +1 more source
Generalized Domain Adaptation [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Accepted by CVPR 2021.
Yu Mitsuzumi +3 more
openaire +2 more sources
Pivot-Guided Embedding for Domain Generalization
IEEE Access, 2022 Neural networks have suffered from a distribution gap between training and test data, known as domain shift. Domain generalization (DG) methods aim to learn domain invariant representations only with limited source domain data to cope with unseen target ...
Hyun Seok Seong +3 more
doaj +1 more source
Domain Generalization Model of Deep Convolutional Networks Based on SAND-Mask
Algorithms, 2022 In the actual operation of the machine, due to a large number of operating conditions and a wide range of operating conditions, the data under many operating conditions cannot be obtained.
Jigang Wang, Liang Chen, Rui Wang
doaj +1 more source
Adversarial Reconstruction Loss for Domain Generalization
IEEE Access, 2021 The biggest fear when deploying machine learning models to the real world is their ability to handle the new data. This problem is significant especially in medicine, where models trained on rich high-quality data extracted from large hospitals do not ...
Imad Eddine Ibrahim Bekkouch +5 more
doaj +1 more source
Learning to Generate Novel Domains for Domain Generalization [PDF]
, 2020 This paper focuses on domain generalization (DG), the task of learning from multiple source domains a model that generalizes well to unseen domains. A main challenge for DG is that the available source domains often exhibit limited diversity, hampering the model's ability to learn to generalize.
Zhou, Kaiyang +3 more
openaire +4 more sources
Domain Generalization via Adversarially Learned Novel Domains
IEEE Access, 2022 This study focuses on the domain generalization task, which aims to learn a model that generalizes to unseen domains by utilizing multiple training domains.
Yu Zhe +3 more
doaj +1 more source
CROSS-DOMAIN TRANSFER OF DEFECT FEATURES IN TECHNICAL DOMAINS BASED ON PARTIAL TARGET DATA
International Journal of Prognostics and Health Management, 2023 A common challenge in real-world classification scenarios with sequentially appending target domain data is insufficient training datasets during the training phase.
Tobias Schlagenhauf, Tim Scheurenbrand
doaj +1 more source
Domain Generalization for Language-Independent Automatic Speech Recognition
Frontiers in Artificial Intelligence, 2022 A language-independent automatic speech recognizer (ASR) is one that can be used for phonetic transcription in languages other than the languages in which it was trained.
Heting Gao +6 more
doaj +1 more source