Dataset Distillation with Infinitely Wide Convolutional Networks

27 July 2021

Papers citing "Dataset Distillation with Infinitely Wide Convolutional Networks"

50 / 161 papers shown

Title
Distill Gold from Massive Ores: Efficient Dataset Distillation via Critical Samples Selection Yue Xu Yong-Lu Li Kaitong Cui Ziyu Wang Cewu Lu Yu-Wing Tai Chi-Keung Tang DD 33 8 0 28 May 2023
Summarizing Stream Data for Memory-Constrained Online Continual Learning Jianyang Gu Kai Wang Wei Jiang Yang You DD 24 9 0 26 May 2023
On the Size and Approximation Error of Distilled Sets Alaa Maalouf M. Tukan Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 29 4 0 23 May 2023
A Survey on Dataset Distillation: Approaches, Applications and Future Directions Jiahui Geng Zongxiong Chen Yuandou Wang Herbert Woisetschlaeger Sonja Schimmler Ruben Mayer Zhiming Zhao Chunming Rong DD 57 26 0 03 May 2023
Generalizing Dataset Distillation via Deep Generative Prior George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu DD 91 84 0 02 May 2023
TRAK: Attributing Model Behavior at Scale Sung Min Park Kristian Georgiev Andrew Ilyas Guillaume Leclerc A. Madry TDI 30 127 0 24 Mar 2023
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples Ben Adlam Jaehoon Lee Shreyas Padhy Zachary Nado Jasper Snoek 13 11 0 09 Mar 2023
Provable Data Subset Selection For Efficient Neural Network Training M. Tukan Samson Zhou Alaa Maalouf Daniela Rus Vladimir Braverman Dan Feldman MLT 23 9 0 09 Mar 2023
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning Ziheng Qin K. Wang Zangwei Zheng Jianyang Gu Xiang Peng ... Daquan Zhou Lei Shang Baigui Sun Xuansong Xie Yang You 116 46 0 08 Mar 2023
DiM: Distilling Dataset into Generative Model Kai Wang Jianyang Gu Daquan Zhou Zheng Hua Zhu Wei Jiang Yang You DD 45 40 0 08 Mar 2023
DREAM: Efficient Dataset Distillation by Representative Matching Yanqing Liu Jianyang Gu Kai Wang Zheng Hua Zhu Wei Jiang Yang You DD 31 76 0 28 Feb 2023
Dataset Distillation with Convexified Implicit Gradients Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 29 41 0 13 Feb 2023
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus DD 28 5 0 02 Feb 2023
Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillation Margarita Vinaroz M. Park DD 20 0 0 31 Jan 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 39 121 0 17 Jan 2023
A Comprehensive Survey of Dataset Distillation Shiye Lei Dacheng Tao DD 31 87 0 13 Jan 2023
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 45 73 0 11 Jan 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 31 27 0 03 Jan 2023
Accelerating Dataset Distillation via Model Augmentation Lei Zhang Jie M. Zhang Bowen Lei Subhabrata Mukherjee Xiang Pan Bo-Lu Zhao Caiwen Ding Y. Li Dongkuan Xu DD 34 62 0 12 Dec 2022
Decentralized Learning with Multi-Headed Distillation A. Zhmoginov Mark Sandler Nolan Miller Gus Kristiansen Max Vladymyrov FedML 32 4 0 28 Nov 2022
Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation Jiawei Du Yiding Jiang Vincent Y. F. Tan Joey Tianyi Zhou Haizhou Li DD 35 109 0 20 Nov 2022
Towards Robust Dataset Learning Yihan Wu Xinda Li Florian Kerschbaum Heng Huang Hongyang R. Zhang DD OOD 41 10 0 19 Nov 2022
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory Justin Cui Ruochen Wang Si Si Cho-Jui Hsieh DD 20 129 0 19 Nov 2022
Black-box Coreset Variational Inference Dionysis Manousakas H. Ritter Theofanis Karaletsos BDL 9 4 0 04 Nov 2022
Dataset Distillation via Factorization Songhua Liu Kai Wang Xingyi Yang Jingwen Ye Xinchao Wang DD 124 141 0 30 Oct 2022
Efficient Dataset Distillation Using Random Feature Approximation Noel Loo Ramin Hasani Alexander Amini Daniela Rus DD 69 95 0 21 Oct 2022
Efficient Bi-Level Optimization for Recommendation Denoising Zongwei Wang Min Gao Wentao Li Junliang Yu Linxin Guo Hongzhi Yin 11 27 0 19 Oct 2022
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities Brian Bartoldson B. Kailkhura Davis W. Blalock 29 47 0 13 Oct 2022
On Divergence Measures for Bayesian Pseudocoresets Balhae Kim J. Choi Seanie Lee Yoonho Lee Jung-Woo Ha Juho Lee DD 8 11 0 12 Oct 2022
Few-shot Backdoor Attacks via Neural Tangent Kernels J. Hayase Sewoong Oh 30 21 0 12 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 39 16 0 11 Oct 2022
Dataset Distillation Using Parameter Pruning Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 36 20 0 29 Sep 2022
Fast Neural Kernel Embeddings for General Activations Insu Han A. Zandieh Jaehoon Lee Roman Novak Lechao Xiao Amin Karbasi 48 18 0 09 Sep 2022
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments Rui Song Dai Liu Da Chen Andreas Festag Carsten Trinitis Martin Schulz Alois C. Knoll DD FedML 23 61 0 24 Aug 2022
Dataset Condensation with Latent Space Knowledge Factorization and Sharing Haebeom Lee Dong Bok Lee Sung Ju Hwang DD 21 37 0 21 Aug 2022
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization Xingyou Song Sagi Perel Chansoo Lee Greg Kochanski Daniel Golovin 29 26 0 27 Jul 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 36 18 0 24 Jul 2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Yuanhao Xiong Ruochen Wang Minhao Cheng Felix X. Yu Cho-Jui Hsieh FedML DD 36 82 0 20 Jul 2022
DC-BENCH: Dataset Condensation Benchmark Justin Cui Ruochen Wang Si Si Cho-Jui Hsieh DD 29 72 0 20 Jul 2022
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland AAML 29 27 0 25 Jun 2022
Fast Finite Width Neural Tangent Kernel Roman Novak Jascha Narain Sohl-Dickstein S. Schoenholz AAML 18 52 0 17 Jun 2022
Condensing Graphs via One-Step Gradient Matching Wei Jin Xianfeng Tang Haoming Jiang Zheng Li Danqing Zhang Jiliang Tang Bin Ying DD 25 98 0 15 Jun 2022
Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks Zhiwei Deng Olga Russakovsky FedML DD 28 92 0 06 Jun 2022
Infinite Recommendation Networks: A Data-Centric Approach Noveen Sachdeva Mehak Preet Dhaliwal Carole-Jean Wu Julian McAuley DD 31 28 0 03 Jun 2022
Dataset Distillation using Neural Feature Regression Yongchao Zhou E. Nezhadarya Jimmy Ba DD FedML 39 149 0 01 Jun 2022
Privacy for Free: How does Dataset Condensation Help Privacy? Tian Dong Bo-Lu Zhao Lingjuan Lyu DD 20 113 0 01 Jun 2022
Dataset Condensation via Efficient Synthetic-Data Parameterization Jang-Hyun Kim Jinuk Kim Seong Joon Oh Sangdoo Yun Hwanjun Song Joonhyun Jeong Jung-Woo Ha Hyun Oh Song DD 388 158 0 30 May 2022
Dataset Pruning: Reducing Training Data by Examining Generalization Influence Shuo Yang Zeke Xie Hanyu Peng Minjing Xu Mingming Sun P. Li DD 149 106 0 19 May 2022
Synthesizing Informative Training Samples with GAN Bo-Lu Zhao Hakan Bilen DD 21 74 0 15 Apr 2022
Information-theoretic Online Memory Selection for Continual Learning Shengyang Sun Daniele Calandriello Huiyi Hu Ang Li Michalis K. Titsias CLL 9 49 0 10 Apr 2022