Three Studies on Learning to Learn in Finland: Anti-Flynn Effects 2001–2017
Sign Up to like & getrecommendations! Published in 2020 at "Scandinavian Journal of Educational Research"
DOI: 10.1080/00313831.2020.1833240
Abstract: Finland is known for its high-performing educational system, but local assessments have shown that performance has declined during the past decade. We report the results of nationally representativ... read more here.
Keywords: finland anti; finland; three studies; learning learn ... See more keywords
The use of methods for learning to learn for students with special needs in Slovenia
Sign Up to like & getrecommendations! Published in 2019 at "European Journal of Special Needs Education"
DOI: 10.1080/08856257.2018.1451294
Abstract: Abstract The purpose of this study is to evaluate the quality of instruction among professionals who implement additional professional support for students with special needs in Slovenia, with a focus on methods for learning to… read more here.
Keywords: students special; needs slovenia; use methods; methods learning ... See more keywords
Learning to Learn: Hierarchical Meta-Critic Networks
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2914469
Abstract: In recent years, deep reinforcement learning methods have achieved impressive performance in many different fields, including playing games, robotics, and dialogue systems. However, there are still a lot of restrictions here, one of which is… read more here.
Keywords: learn hierarchical; meta critic; meta; learning learn ... See more keywords
Learning to Learn Variational Quantum Algorithm.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3151127
Abstract: Variational quantum algorithms (VQAs) use classical computers as the quantum outer loop optimizer and update the circuit parameters to obtain an approximate ground state. In this article, we present a meta-learning variational quantum algorithm (meta-VQA)… read more here.
Keywords: quantum; quantum algorithm; learn variational; variational quantum ... See more keywords
Learning to Learn and Sample BRDFs
Sign Up to like & getrecommendations! Published in 2022 at "Computer Graphics Forum"
DOI: 10.1111/cgf.14754
Abstract: We propose a method to accelerate the joint process of physically acquiring and learning neural Bi‐directional Reflectance Distribution Function (BRDF) models. While BRDF learning alone can be accelerated by meta‐learning, acquisition remains slow as it… read more here.
Keywords: sample brdfs; brdfs; learn sample; learning learn ... See more keywords
Learning “How to Learn”: Super Declarative Motor Learning Is Impaired in Parkinson's Disease
Sign Up to like & getrecommendations! Published in 2017 at "Neural Plasticity"
DOI: 10.1155/2017/3162087
Abstract: Learning new information is crucial in daily activities and occurs continuously during a subject's lifetime. Retention of learned material is required for later recall and reuse, although learning capacity is limited and interference between consecutively… read more here.
Keywords: interference; impaired parkinson; parkinson disease; retention ... See more keywords
Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Computational Neuroscience"
DOI: 10.3389/fncom.2022.885207
Abstract: Neuroscience models commonly have a high number of degrees of freedom and only specific regions within the parameter space are able to produce dynamics of interest. This makes the development of tools and strategies to… read more here.
Keywords: neuroscience; optimization; parameter; neuroscience models ... See more keywords
Meta-SpikePropamine: learning to learn with synaptic plasticity in spiking neural networks
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2023.1183321
Abstract: We propose that in order to harness our understanding of neuroscience toward machine learning, we must first have powerful tools for training brain-like models of learning. Although substantial progress has been made toward understanding the… read more here.
Keywords: neural networks; spiking neural; plasticity; learning ... See more keywords