Results 41 to 50 of about 9,064 (165)
Optimizing Seizure Prediction From Reduced Scalp EEG Channels Based on Spectral Features and MAML
IEEE Access, 2021 Epilepsy is a severe neurological disease with high prevalence and morbidity worldwide. The unpredictability of seizures prevents physicians from tailoring drugs and therapies.
Anibal Romney, Vidya Manian
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Meta-Learning by the Baldwin Effect
, 2018 The scope of the Baldwin effect was recently called into question by two papers that closely examined the seminal work of Hinton and Nowlan. To this date there has been no demonstration of its necessity in empirically challenging tasks. Here we show that
Fernando, Chrisantha Thomas +8 more
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, 2018 The field of few-shot learning has recently seen substantial advancements. Most of these advancements came from casting few-shot learning as a meta-learning problem. Model Agnostic Meta Learning or MAML is currently one of the best approaches for few-shot learning via meta-learning.
Antoniou, Antreas +2 more
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A meta-learning approach to improving transferability for freeway traffic crash risk prediction
Digital Transportation and SafetyCrash risk prediction plays a vital role in preventing freeway traffic accidents. Due to the limited availability of crash data in some freeway sections, model transferability of crash risk prediction has become an essential topic in traffic safety ...
Chenlei Liao, Xiqun (Michael) Chen
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Few shot learning for Korean winter temperature forecasts
npj Climate and Atmospheric ScienceTo address the challenge of limited training samples, this study employs the model-agnostic meta-learning (MAML) algorithm along with domain-knowledge-based data augmentation to predict winter temperatures on the Korean Peninsula. While data augmentation
Seol-Hee Oh, Yoo-Geun Ham
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Syrian Journal for Science and InnovationData annotation is a time-consuming and labor-intensive process in classification tasks. Recently, numerous studies have explored the few-shot learning approach using meta-learning, particularly the MAML algorithm.
Shadi Balloul +2 more
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Labeled Memory Networks for Online Model Adaptation
, 2017 Augmenting a neural network with memory that can grow without growing the number of trained parameters is a recent powerful concept with many exciting applications.
Sarawagi, Sunita, Shankar, Shiv
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Wormhole MAML: Meta-Learning in Glued Parameter Space
, 2022 In this paper, we introduce a novel variation of model-agnostic meta-learning, where an extra multiplicative parameter is introduced in the inner-loop adaptation. Our variation creates a shortcut in the parameter space for the inner-loop adaptation and increases model expressivity in a highly controllable manner.
Chang, Chih-Jung Tracy +2 more
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The FEBS Journal, EarlyView.Divalent metal transporter 1 (Dmt1) maintains iron homeostasis and lysosomal proteostasis required for physiological Notch receptor–ligand signaling. Dmt1 loss lowers iron storage capacity (ferritin), increasing intracellular Fe2+, driving ROS and lipid peroxidation, and leading to lysosomal/mitochondrial dysfunction.
Rui Zhang +5 more
wiley +1 more source
Task Transfer by Preference-Based Cost Learning
, 2019 The goal of task transfer in reinforcement learning is migrating the action policy of an agent to the target task from the source task. Given their successes on robotic action planning, current methods mostly rely on two requirements: exactly-relevant ...
Huang, Wenbing +4 more
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