Results 51 to 60 of about 1,979,450 (271)
A survey on heterogeneous transfer learning
Journal of Big Data, 2017 Transfer learning has been demonstrated to be effective for many real-world applications as it exploits knowledge present in labeled training data from a source domain to enhance a model’s performance in a target domain, which has little or no labeled ...
Oscar Day, Taghi M. Khoshgoftaar
doaj +1 more source
How Transferable are Neural Networks in NLP Applications?
, 2016 Transfer learning is aimed to make use of valuable knowledge in a source domain to help model performance in a target domain. It is particularly important to neural networks, which are very likely to be overfitting.
Jin, Zhi +6 more
core +1 more source
Transferable learning on analog hardware
Science Advances, 2023 While analog neural network (NN) accelerators promise massive energy and time savings, an important challenge is to make them robust to static fabrication error. Present-day training methods for programmable photonic interferometer circuits, a leading analog NN platform, do not produce networks that perform well in the presence of static hardware ...
Sri Krishna Vadlamani +2 more
openaire +3 more sources
Molecular Oncology, EarlyView.Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee +8 more
wiley +1 more source
Climate Resilience and SustainabilityClimate change is threatening the resilience of smallholder agroecosystems in semi‐arid areas. Wetland agroecosystems provide critical life support and positive outcomes for people, nature and climate in semi‐arid areas.
Pascal Manyakaidze +2 more
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The Impact of Culture on Learning Transfer in Burkina Faso and Ghana
AS: Andragoška Spoznanja, 2022 Culture is a predominant force in people’s lives that impacts learning and thus culture influences learning transfer. Because working across nations has become the norm and every year billions of dollars are spent on professional learning around the ...
Corinne Brion
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Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning [PDF]
, 2020 We propose a novel adaptive transfer learning framework, learning to transfer learn (L2TL), to improve performance on a target dataset by careful extraction of the related information from a source dataset. Our framework considers cooperative optimization of shared weights between models for source and target tasks, and adjusts the constituent loss ...
Zhu, Linchao +3 more
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Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Multilingual Meta-Transfer Learning for Low-Resource Speech Recognition
IEEE AccessThis paper proposes a novel meta-transfer learning method to improve automatic speech recognition (ASR) performance in low-resource languages. Nowadays, we are witnessing high interest in low-resource ASR tasks aiming at delivering feasible and reliable ...
Rui Zhou +4 more
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FEBS Open Bio, EarlyView.Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source