Dataset Distillation by Matching Training Trajectories

22 March 2022

Antonio Torralba

Jun-Yan Zhu

Papers citing "Dataset Distillation by Matching Training Trajectories"

50 / 259 papers shown

Title
Too Large; Data Reduction for Vision-Language Pre-Training Alex Jinpeng Wang Kevin Qinghong Lin David Junhao Zhang Stan Weixian Lei Mike Zheng Shou VLM 30 24 0 31 May 2023
Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching Tao Feng Jie Zhang Peizheng Wang Zhijie Wang Shengyuan Pang DD 53 0 0 29 May 2023
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning Patrik Okanovic R. Waleffe Vasilis Mageirakos Konstantinos E. Nikolakakis Amin Karbasi Dionysis Kalogerias Nezihe Merve Gürel Theodoros Rekatsinas DD 45 12 0 28 May 2023
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 34 4 0 23 May 2023
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness Zongxiong Chen Jiahui Geng Derui Zhu Herbert Woisetschlaeger Qing Li Sonja Schimmler Ruben Mayer Chunming Rong DD 26 9 0 05 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
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies Oscar Li James Harrison Jascha Narain Sohl-Dickstein Virginia Smith Luke Metz 46 5 0 21 Apr 2023
Class-Incremental Exemplar Compression for Class-Incremental Learning Zilin Luo Yaoyao Liu Bernt Schiele Qianru Sun VLM CLL 91 44 0 24 Mar 2023
Bayesian Pseudo-Coresets via Contrastive Divergence Piyush Tiwary Kumar Shubham V. Kashyap Prathosh A.P. 21 3 0 20 Mar 2023
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning Ziheng Qin Kaidi Wang Zangwei Zheng Jianyang Gu Xiang Peng ... Daquan Zhou Lei Shang Baigui Sun Xuansong Xie Yang You 124 47 0 08 Mar 2023
DiM: Distilling Dataset into Generative Model Kai Wang Jianyang Gu Daquan Zhou Zheng Hua Zhu Wei Jiang Yang You DD 51 40 0 08 Mar 2023
Distillation from Heterogeneous Models for Top-K Recommendation SeongKu Kang Wonbin Kweon Dongha Lee Jianxun Lian Xing Xie Hwanjo Yu VLM 32 21 0 02 Mar 2023
DREAM: Efficient Dataset Distillation by Representative Matching Yanqing Liu Jianyang Gu Kai Wang Zheng Hua Zhu Wei Jiang Yang You DD 36 76 0 28 Feb 2023
Dataset Distillation with Convexified Implicit Gradients Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 31 41 0 13 Feb 2023
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations Hui-Po Wang Dingfan Chen Raouf Kerkouche Mario Fritz FedML DD 20 4 0 02 Feb 2023
Knowledge Distillation on Graphs: A Survey Yijun Tian Shichao Pei Xiangliang Zhang Chuxu Zhang Nitesh V. Chawla 21 28 0 01 Feb 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 53 121 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 34 28 0 03 Jan 2023
Fake it till you make it: Learning transferable representations from synthetic ImageNet clones Mert Bulent Sariyildiz Alahari Karteek Diane Larlus Yannis Kalantidis DiffM VLM 32 153 0 16 Dec 2022
Accelerating Dataset Distillation via Model Augmentation Lei Zhang Jie M. Zhang Bowen Lei Subhabrata Mukherjee Xiang Pan Bo-Lu Zhao Caiwen Ding Heng Chang Dongkuan Xu DD 43 62 0 12 Dec 2022
Decentralized Learning with Multi-Headed Distillation A. Zhmoginov Mark Sandler Nolan Miller Gus Kristiansen Max Vladymyrov FedML 37 4 0 28 Nov 2022
Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation Jiawei Du Yiding Jiang Vincent Y. F. Tan Qiufeng Wang Haizhou Li DD 35 109 0 20 Nov 2022
DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi Weizhong Zhang Yueqi Xie Jiahui Gao Xiaoyu Wang Sunghun Kim Qifeng Chen DD 39 26 0 20 Nov 2022
Towards Robust Dataset Learning Yihan Wu Xinda Li Florian Kerschbaum Heng Huang Hongyang R. Zhang DD OOD 43 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 22 129 0 19 Nov 2022
Iterative Teaching by Data Hallucination Zeju Qiu Weiyang Liu Tim Z. Xiao Zhen Liu Umang Bhatt Yucen Luo Adrian Weller Bernhard Schölkopf 29 9 0 31 Oct 2022
Dataset Distillation via Factorization Songhua Liu Kai Wang Xingyi Yang Jingwen Ye Xinchao Wang DD 126 141 0 30 Oct 2022
A Survey of Dataset Refinement for Problems in Computer Vision Datasets Zhijing Wan Zhixiang Wang CheukTing Chung Zheng Wang 36 8 0 21 Oct 2022
MaSS: Multi-attribute Selective Suppression Chun-Fu Chen Shaohan Hu Zhong-Zhi Shi Prateek Gulati Bill Moriarty Marco Pistoia Vincenzo Piuri P. Samarati CVBM 8 4 0 18 Oct 2022
On Divergence Measures for Bayesian Pseudocoresets Balhae Kim J. Choi Seanie Lee Yoonho Lee Jung-Woo Ha Juho Lee DD 19 11 0 12 Oct 2022
Meta Knowledge Condensation for Federated Learning Ping Liu Xin Yu Qiufeng Wang DD FedML 30 28 0 29 Sep 2022
Model Zoos: A Dataset of Diverse Populations of Neural Network Models Konstantin Schurholt Diyar Taskiran Boris Knyazev Xavier Giró-i-Nieto Damian Borth 52 29 0 29 Sep 2022
Compressed Gastric Image Generation Based on Soft-Label Dataset Distillation for Medical Data Sharing Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 32 40 0 29 Sep 2022
Dataset Distillation Using Parameter Pruning Guang Li Ren Togo Takahiro Ogawa Miki Haseyama DD 42 20 0 29 Sep 2022
Learning to Learn with Generative Models of Neural Network Checkpoints William S. Peebles Ilija Radosavovic Tim Brooks Alexei A. Efros Jitendra Malik UQCV 75 64 0 26 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
DC-BENCH: Dataset Condensation Benchmark Justin Cui Ruochen Wang Si Si Cho-Jui Hsieh DD 34 72 0 20 Jul 2022
PRANC: Pseudo RAndom Networks for Compacting deep models Parsa Nooralinejad Ali Abbasi Soroush Abbasi Koohpayegani Kossar Pourahmadi Meibodi Rana Muhammad Shahroz Khan Soheil Kolouri Hamed Pirsiavash DD 32 0 0 16 Jun 2022
Condensing Graphs via One-Step Gradient Matching Wei Jin Xianfeng Tang Haoming Jiang Zheng Li Danqing Zhang Jiliang Tang Bin Ying DD 31 98 0 15 Jun 2022
Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks Zhiwei Deng Olga Russakovsky FedML DD 35 92 0 06 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 24 113 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 393 158 0 30 May 2022
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning Jiahui Gao Renjie Pi Yong Lin Hang Xu Jiacheng Ye Zhiyong Wu Weizhong Zhang Xiaodan Liang Zhenguo Li Lingpeng Kong SyDa VLM 67 45 0 25 May 2022