Fast-learnerReinforcement learningPrefrontal cortexSlow-learnerWe present a neuro-computational model that, based on brain principles, succeeds in performing a category learning task. In particular, the network includes a fast learner (the basal ganglia) that via...
Slownetwork和Fast network异步进行,提高计算效率。 2、在有限资源的硬件设备上布置性能良好的网络,就需要对网络模型进行压缩和加速,其中量化模型是一种高效手段。基于[2]算法,论文的ConvLSTM单元在数学运算(addition,multiplication, sigmoid and ReLU6)后插入量化计算,确保拼接操作的输入范围相同,消除重新缩放的需求。 3...
{mcclelland1995there} in neuroscience, humans do effective \emph{continual learning} through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics and individual experiences, and a slow learning system located in the neocortex for the ...
In contrast, standard deep Reinforcement Learning algorithms rely on a neural network not only to generalise plans, but to discover them too. We show that ExIt outperforms REINFORCE for training a neural network to play the board game Hex, and our final tree search agent, trained tabula rasa,...
At least half a dozen other prominent institutions, such as the Annenberg Foundation and the Pew Charitable Trust, joined the effort, as did the U.S. Department of Education’s Smaller Learning Communities Program.霍华德·韦纳和哈里斯·兹维尔林的论文得到了 盖茨基金会一项高达17亿美元的大型研究投资...
✔︎Conclusion:Fast Learning is enabled by slow learning. (这个挺make sense的,毕竟对于人类也是一样的,冷启动学习总是慢的) 4 Meta-RL: Speeding up Deep RL by Learning to Learn 前文中提到了缩小假设空间(hypothesis set)可以加快学习,但这个是基于引入的strong inductive biases 是满足我们最终要学会...
The test of learning psychology is whether your understanding of situations you encounter has changed, not whether you have learned a new fact. There is a deep gap between our thinking about statistics and our thinking about individual cases. Statistical results with a causal interpretation have a...
Biological data suggest that a synergy of synaptic plasticity on a slow time scale with network dynamics on a faster time scale is responsible for fast learning capabilities of the brain. We show here that a suitable orchestration of this synergy between synaptic plasticity and network dynamics ...
Fast and Slow RL: Broader Implications 在讨论回合式RL和元RL时,我们强调了“缓慢”学习在实现快速且样本高效的学习中的作用。如我们所见,在元RL中,基于权重的缓慢学习的作用是建立归纳偏差,该偏差可以指导推断,从而支持快速适应新任务。缓慢的增量学习在回合式RL中的作用可以用相关术语来理解。回合式RL本质上取决...
Code for CVPR 2024 paper Interactive Continual Learning: Fast and Slow Thinking Dependencies pip install -r requirements.txt Dataset Preparation For CIFAR10 and CIFAR100 datasets, the script automatically downloads. For ImageNet-R dataset refer to the following link: https://github.com/hendrycks/im...