Results 51 to 60 of about 271,594 (275)

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

Modeling Task Uncertainty for Safe Meta-Imitation Learning

Frontiers in Robotics and AI, 2020
To endow robots with the flexibility to perform a wide range of tasks in diverse and complex environments, learning their controller from experience data is a promising approach.
Tatsuya Matsushima, Naruya Kondo, Yusuke Iwasawa, Kaoru Nasuno, Kaoru Nasuno, Yutaka Matsuo   +5 more
doaj   +1 more source

Task-Covariant Representations for Few-Shot Learning on Remote Sensing Images

Mathematics, 2023
In the regression and classification of remotely sensed images through meta-learning, techniques exploit task-invariant information to quickly adapt to new tasks with fewer gradient updates.
Liyi Zhang, Zengguang Tian, Yi Tang, Zuo Jiang   +3 more
doaj   +1 more source

Towards Meta-learning over Data Streams [PDF]

, 2014
Modern society produces vast streams of data. Many stream mining algorithms have been developed to capture general trends in these streams, and make predictions for future observations, but relatively little is known about which algorithms perform ...
Holmes, Geoffrey, Pfahringer, Bernhard, van Rijn, Jan N., Vanschoren, Joaquin   +3 more
core   +1 more source

Online Meta-learning by Parallel Algorithm Competition

, 2017
The efficiency of reinforcement learning algorithms depends critically on a few meta-parameters that modulates the learning updates and the trade-off between exploration and exploitation.
Baker James E., Bertsekas D. P., Downey Carlton, Gabillon V., Goodfellow Ian, Mnih Volodymyr, Snoek Jasper, Snoek Jasper, Springenberg Jost T., Sutton S., Sutton S., Szita I., Unemi T., Wu Jian   +13 more
core   +1 more source

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source

Fairness-aware recommendation with meta learning

Scientific Reports
Fairness has become a critical value online, and the latest studies consider it in many problems. In recommender systems, fairness is important since the visibility of items is controlled by systems.
Hyeji Oh, Chulyun Kim
doaj   +1 more source

A Time Series Forecasting Approach Based on Meta-Learning for Petroleum Production under Few-Shot Samples

Energies
Accurate prediction of crude petroleum production in oil fields plays a crucial role in analyzing reservoir dynamics, formulating measures to increase production, and selecting ways to improve recovery factors.
Zhichao Xu, Gaoming Yu
doaj   +1 more source

Meta-learning with Network Pruning [PDF]

, 2020
Meta-learning is a powerful paradigm for few-shot learning. Although with remarkable success witnessed in many applications, the existing optimization based meta-learning models with over-parameterized neural networks have been evidenced to ovetfit on training tasks.
Tian, Hongduan, Liu, Bo, Yuan, Xiao-Tong, Liu, Qingshan   +3 more
openaire   +2 more sources

Effects of causal beliefs about gout on public views about gout management: A randomized experimental study

Arthritis Care &Research, Accepted Article.
Objective Despite well‐described biological causes, the public views unhealthy lifestyle choices as the primary cause of gout. This study investigated how causal beliefs about gout influence the public's views about its management. Methods In a randomized study, 201 members of the public viewed one of two 2‐minute videos about gout.
Rachel Murdoch, Borislav Mihov, Anne Horne, Keith J. Petrie, Gregory D. Gamble, Lachlan Fleck, Nicola Dalbeth   +6 more
wiley   +1 more source