no code implementations • 8 Apr 2023 • Shanglin Zhou, Mikhail A. Bragin, Lynn Pepin, Deniz Gurevin, Fei Miao, Caiwen Ding
We evaluate our method on image classification tasks using CIFAR-10 and ImageNet with state-of-the-art MLP-Mixer, Swin Transformer, and VGG-16, ResNet-18, ResNet-50 and ResNet-110, MobileNetV2.
1 code implementation • 8 Oct 2022 • Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan
Prior work operates on pre-collected temporal graph data and is not designed to handle updates on a graph in real-time.
1 code implementation • 11 Sep 2022 • Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding
In this paper, we utilize two state-of-the-art model compression methods (1) train and prune and (2) sparse training for the sparsification of weight layers in GNNs.
no code implementations • 18 Dec 2020 • Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail Bragin, Caiwen Ding, Fei Miao
We further accelerate the convergence of the SLR by using quadratic penalties.
1 code implementation • 18 Jun 2020 • Kaleel Mahmood, Deniz Gurevin, Marten van Dijk, Phuong Ha Nguyen
We provide this large scale study and analyses to motivate the field to move towards the development of more robust black-box defenses.