meta learningwithout memorization。通过引入互信息作为正则项，避免出现任务过拟合的现象。这就好比让他学...
44. Meta-Learning without Memorization 会议:ICLR 2020. 作者:Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn 链接:https://openreview.net/pdf?id=BklEFpEYwS 45. Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization 会议:ICLR 2020. 作者:Michael Vol...
meta_optimizer.step()# Meta-optimizer step Avoid memory blow-up — Hidden State Memorization 有时我们想学习一个优化器,该优化器可以在具有数千万参数的超大型模型上运行,同时我们想通过大量步骤来展开元训练,以获得高质量的梯度,例如我们在工作中做到了。 实际上,这意味着我们要在元前传过程中包括很长的训练...
Meta-Learning without Memorization [paper] Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn --ICLR 2020 Meta-Amortized Variational Inference and Learning [paper] Mike Wu, Kristy Choi, Noah Goodman, Stefano Ermon --arXiv 2019 ...
Capability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization. Red teaming For both scenarios, we conducted recurring red teaming exercises with the goal...
Capability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization. Red teaming For both scenarios, we conducted recurring red teaming exercises with the goal...
As a deep-learning model may require large amounts of data to train and may have the capacity to overfit to the errors existing in the data due to the “memorization effect”, the quality of the model may be highly dependent on the quality of the data. As an example and not by way ...
Emergent in-context learning with Transformers is exciting! But what is necessary to make neural nets implement general-purpose in-context learning? 2^14 tasks, a large model + memory, and initial memorization to aid generalization. Full paperhttps://t.co/yyp9467WgF ...
(i.e. cost of representing a program). Both components are necessary—lesions sensitive to just one of the two components dramatically underperform the full model (Fig.5C). The program prior encourages generalization and discourages memorization. The metaprogram prior may help MPL assign credit to...
71 7.33 Learning To Remember More With Less Memorization 7, 8, 7 0.47 Accept (Oral) 72 7.33 Gan Dissection: Visualizing And Understanding Generative Adversarial Networks 7, 7, 8 0.47 Accept (Poster) 73 7.33 Detecting Egregious Responses In Neural Sequence-to-sequence Models 7, 7, 8 0.47 Acce...