Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy

Large convolutional neural networks (CNN) can be difficult to train in the differentially private (DP) regime, since the optimization algorithms require a computationally expensive operation, known as the per-sample gradient clipping. We propose an efficient and scalable implementation of this clipping on convolutional layers, termed as the mixed ghost clipping, that significantly eases the private training in terms of both time and space complexities, without affecting the accuracy. The improvement in efficiency is rigorously studied through the first complexity analysis for the mixed ghost clipping and existing DP training algorithms. Extensive experiments on vision classification tasks, with large ResNet, VGG, and Vision Transformers, demonstrate that DP training with mixed ghost clipping adds $1\sim 10\%$ memory overhead and $<2\times$ slowdown to the standard non-private training. Specifically, when training VGG19 on CIFAR10, the mixed ghost clipping is $3\times$ faster than state-of-the-art Opacus library with $18\times$ larger maximum batch size. To emphasize the significance of efficient DP training on convolutional layers, we achieve 96.7\% accuracy on CIFAR10 and 83.0\% on CIFAR100 at $\epsilon=1$ using BEiT, while the previous best results are 94.8\% and 67.4\%, respectively. We open-source a privacy engine (\url{https://github.com/JialinMao/private_CNN}) that implements DP training of CNN with a few lines of code.Comment: Accepted to NeurIPS 202

Users’ Emotional Attachments to Internet Celebrities: Based on the Perspective of Extended-self

Although previous researcher has focused on the use of social media between celebrities and fans from the use and gratification perspective, knowledge on why users stick with live streaming is limited. Therefore, the authors propose that sticking with live streaming reflects a strong connection between celebrities and users. We define emotional attachment as the strength of the cognitive and emotional bond connecting the celebrities with the self. Consequently, in this study, we adopt attachment theory to investigate users’ tendency to stick with live streaming from the extended-self perspective. The findings of this study fully support the hypotheses specifying the relationships between constructs. Emotional attachment was influenced by gratifying the self, enriching the self and enabling the self, and which in turn are strong predictors of users’ stickiness intention. The current research contributes to the further expansion of social media research and applied attachment theory into the live streaming context

Measurement and Simulation Study on Effective Drainage Radius of Borehole Along Coal Seam

A measurement study was conducted for the effective drainage radius of borehole along coal seam #9 of the Kaiyuan Coal Mine using the gas pressure method and gas flow method. The measurement results show that the effective drainage radius of borehole along coal seam #9 was 0.75 m, 27 days after drainage, and 1.5 m, 92 days after drainage. Experimental schemes were designed for the entire evolution of the stress in the coal mass around the borehole, and an experimental study on methane seepage in the coal mass around borehole was conducted. Fitting functions for the permeability of the coal sample and its vertical stress were obtained by fitting the experimental data. Based on the vertical stress–permeability functional relationship of coal masses around borehole, a numerical calculation model for methane seepage from coal masses around borehole was established, and the influences of drainage time, initial gas pressure, borehole diameter, and drainage negative pressure on the effective drainage radius of borehole were investigated. The numerical simulation results show that with the increase in initial gas pressure and borehole diameter, the effective drainage radius of borehole increases continuously but its increase amplitude decreases constantly. With the increase in drainage negative pressure, the effective drainage radius of borehole increases linearly but the increase amplitude is relatively small. The layout parameters of borehole along coal seam #9 of the Kaiyuan Coal Mine were optimized based on the numerical calculation results, and the reasonable drainage time, reasonable borehole diameter, and reasonable drainage negative pressure are 180 days, 120 mm, and 15 kPa, respectively, for the borehole along coal seam #9