Towards Understanding Generalization in Gradient-Based Meta-LearningSimon GuiroyVikas VermaChristopher J. Pal
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes 来自 arXiv.org 喜欢 0 阅读量: 313 作者:L Wu,Z Zhu,E, Weinan 摘要: It is widely observed that deep learning models with learned parameters generalize well, even with much more model parameters than the number ...
《Understanding Contrastive RepresentationLearning through Alignment and Uniformity on the Hypersphere》 提到的alignment和uniform。 (1)alignment,这一点和《Understanding Contrastive RepresentationLearning through Alignment and Uniformity on the Hypersphere》 是一致的,即相似的样本在embedding 空间中应该也是接近的; ...
However, the theoretical understanding of its generalization ability on downstream tasks is not well studied. To this end, we present a theoretical explanation of how contrastive self-supervised pre-trained models generalize to downstream tasks. Concretely, we quantitatively show that the self-supervised...
Optimization approaches for generalization and data abstraction The availability of methods for abstracting and generalizing spatial data is vital for understanding and communicating spatial information. Spatial analysi... M Sester - 《International Journal of Geographical Information Science》 被引量: 111发表...
& Yao, J. Towards better understanding and better generalization of low-shot classification in histology images with contrastive learning. In International Conference on Learning Representations (2021). Tian, Y., Wang, Y., Krishnan, D., Tenenbaum, J. B. & Isola, P. Rethinking few-shot image...
Understanding the flow of information in Deep Neural Networks (DNNs) is a challenging problem that has gain increasing attention over the last few years. While several methods have been proposed to explain network predictions, there have been only a few attempts to compare them from a theoretical...
Understanding the genetic component of Alzheimer’s disease (AD) has been and still is a major research challenge. The main goal is to understand the pathophysiological mechanisms involved, and the characterization of the mutations responsible for monogenic forms of AD illustrates the scale of this ...
ICLR'23 FedDecorr Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning and unofficial implementation of the following papers: VenueMethodPaper Title AISTATS'17 FedAvg Communication-Efficient Learning of Deep Networks from Decentralized Data ArXiv'19 FedAvgM Measuring the...
Although our BriVL is only pre-trained with an image-text matching learning objective, its strong generalization ability has already satisfied some of the key features that an AGI system should have. Importantly, with a couple of model-interpretability tools developed in this work, we manage to ...