Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
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checkpass检测
PaperYY检测
Prioritized training on points that are learnable, worth learning, and not yet learnt
Training on web-scale data can take months. But much computation and time is wasted on
redundant and noisy points that are already learnt or not learnable. To accelerate training …
redundant and noisy points that are already learnt or not learnable. To accelerate training …
Deep sets
We study the problem of designing models for machine learning tasks defined on sets. In
contrast to the traditional approach of operating on fixed dimensional vectors, we consider …
contrast to the traditional approach of operating on fixed dimensional vectors, we consider …
Training deep spiking neural networks using backpropagation
Deep spiking neural networks (SNNs) hold the potential for improving the latency and
energy efficiency of deep neural networks through data-driven event-based computation …
energy efficiency of deep neural networks through data-driven event-based computation …
Unsupervised representation learning with deep convolutional generative adversarial networks
A Radford, L Metz, S Chintala - ar**s in the data. The main proposition is that the first neighbor of each …
Generalized byzantine-tolerant sgd
We propose three new robust aggregation rules for distributed synchronous Stochastic
Gradient Descent~(SGD) under a general Byzantine failure model. The attackers can …
Gradient Descent~(SGD) under a general Byzantine failure model. The attackers can …
One network to solve them all--solving linear inverse problems using deep projection models
While deep learning methods have achieved state-of-the-art performance in many
challenging inverse problems like image inpainting and super-resolution, they invariably …
challenging inverse problems like image inpainting and super-resolution, they invariably …
Adaptive data augmentation for image classification
Data augmentation is the process of generating samples by transforming training data, with
the target of improving the accuracy and robustness of classifiers. In this paper, we propose …
the target of improving the accuracy and robustness of classifiers. In this paper, we propose …