Deep Learning (DL) has had an immense success in the recent past, leading to state-of-the-
art results in various domains, such as image recognition and natural language processing …

Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …

Passing gradient is a widely used scheme in modern multi-node learning system (eg,
distributed training, collaborative learning). In a long time, people used to believe that …

Neural Tangents is a library designed to enable research into infinite-width neural networks.
It provides a high-level API for specifying complex and hierarchical neural network …

We extract pixel-level masks of extreme weather patterns using variants of Tiramisu and
DeepLabv3+ neural networks. We describe improvements to the software frameworks, input …

We demonstrate that training ResNet-50 on ImageNet for 90 epochs can be achieved in 15
minutes with 1024 Tesla P100 GPUs. This was made possible by using a large minibatch …

ThispaperpresentsBigDL (adistributeddeeplearning framework for Apache Spark), which
has been used by a variety of users in the industry for building deep learning applications on …

Training of generative adversarial network (GAN) on a video dataset is a challenge because
of the sheer size of the dataset and the complexity of each observation. In general, the …

Programmable network hardware can run services traditionally deployed on servers,
resulting in orders-of-magnitude improvements in performance. Yet, despite these …

Large-scale distributed training of deep neural networks suffers from the generalization gap
caused by the increase in the effective mini-batch size. Previous approaches try to solve this …