B. R. Vuorio, S.-H. Sun, H. Hu, and J. J. Lim, “Multimodal Model-Agnostic Meta-Learning Via Task-Aware Modulation,” in NeurIPS, 2019. 根据不同的任务选取不同的prior,设计了两个网络,第一个网络用来提取当前任务的类型,将其编码为表征加入到task network层级的参数中。这和c-glow中cond的...
5.3 Neural Architecture Search (NAS) 5.4 Hyper-Parameter Optimization 5.5 Bayesian Meta-Learning 5.6 Unsupervised and Semi-Supervised Meta-Learning 5.7 Continual, Online and Adaptive Learning 5.8 Domain Adaptation and Domain Generalization 5.9 Language and Speech 5.10 Emerging Topics 6 Challenges and Open...
ALVINN (Autonomous Land Vehicle In a Neural Network)是一个基于神经网络的智能系统,通过观察人类的驾驶来学习驾驶,ALVINN能够控制NavLab,装在一辆改装版军用悍马,这辆悍马装载了传感器、计算机和驱动器用来进行自动驾驶的导航试验。实现ALVINN功能的第一步,是对它进行训练,也就是训练一个人驾驶汽车。 然后让ALVINN观看...
[4] Duong, L., Cohn. et.al. 2015. Low Resource Dependency Parsing Cross-Lingual Parameter Sharing in a Neural Network Parser. ACL2015. [5] Yang, Y. et. al. 2017. Trace Norm Regularized Deep Multi-Task Learning. ICLR2017 workshop. [6] Abu-Mostafa, et. al. 1990. Learning from Hint...
ALVINN (Autonomous Land Vehicle In a Neural Network)是一个基于神经网络的智能系统, 通过观察人类的驾驶来学习驾驶,ALVINN 能够控制 NavLab,装在一辆改装版军用悍马,这辆悍马装载了传感器、计算机和驱动器用来进行自动驾驶的导航试验。实现 ALVINN 功能的 第一步,是对它进行训练,也就是训练一个人驾驶汽车。
[1] Shortcut learning in deep neural networks [2] CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet [3] Masked autoencoders are scalable vision learners [4] An image is worth 16x16 words: Transformers for image recognition...
参考文献： [1].Meta-Learning in Neural Networks: A Survey
Neural networks approach the problem in a different way. The idea is to take a large number of handwritten digits, known as training examples, and then develop a system which can learn from those training examples. In other words, the neural network uses the examples to automatically infer rul...
Deep learning neural network expand all in page Description Adlnetworkobject specifies a deep learning neural network architecture. Tip For most deep learning tasks, you can use a pretrained neural network and adapt it to your own data. For an example showing how to use transfer learning to retr...
network trains on a particular task its parameters are adapted to solve the task. When a new task is introduced, new adaptations overwrite the knowledge that the neural network had previously acquired. This phenomenon is known in cognitive science as ‘catastrophic forgetting’, and is considered ...