Dataset Distillation with Infinitely Wide Convolutional Networks

Dataset Distillation with Infinitely Wide Convolutional Networks

27 July 2021

Papers citing "Dataset Distillation with Infinitely Wide Convolutional Networks"

11 / 161 papers shown

Title
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 45 363 0 22 Mar 2022
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks Xin Yu Thiago Serra Srikumar Ramalingam Shandian Zhe 34 48 0 09 Mar 2022
CAFE: Learning to Condense Dataset by Aligning Features Kai Wang Bo-Lu Zhao Xiangyu Peng Zheng Zhu Shuo Yang Shuo Wang Guan Huang Hakan Bilen Xinchao Wang Yang You DD 29 0 0 03 Mar 2022
Dataset Condensation with Contrastive Signals Saehyung Lee Sanghyuk Chun Sangwon Jung Sangdoo Yun Sung-Hoon Yoon DD 11 94 0 07 Feb 2022
Submodularity In Machine Learning and Artificial Intelligence J. Bilmes 8 52 0 31 Jan 2022
When less is more: Simplifying inputs aids neural network understanding R. Schirrmeister Rosanne Liu Sara Hooker T. Ball 24 5 0 14 Jan 2022
The Augmented Image Prior: Distilling 1000 Classes by Extrapolating from a Single Image Yuki M. Asano Aaqib Saeed 30 7 0 01 Dec 2021
Dataset Condensation with Distribution Matching Bo-Lu Zhao Hakan Bilen DD 10 282 0 08 Oct 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 194 288 0 16 Feb 2021
The large learning rate phase of deep learning: the catapult mechanism Aitor Lewkowycz Yasaman Bahri Ethan Dyer Jascha Narain Sohl-Dickstein Guy Gur-Ari ODL 159 234 0 04 Mar 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 228 4,460 0 23 Jan 2020