Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks

6 June 2022

Papers citing "Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks"

26 / 76 papers shown

Title
Farzi Data: Autoregressive Data Distillation Noveen Sachdeva Zexue He Wang-Cheng Kang Jianmo Ni D. Cheng Julian McAuley DD 21 3 0 15 Oct 2023
Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation Haizhong Zheng Jiachen Sun Shutong Wu B. Kailkhura Zhuoqing Mao Chaowei Xiao Atul Prakash DD 24 2 0 11 Oct 2023
Self-Supervised Dataset Distillation for Transfer Learning Dong Bok Lee Seanie Lee Joonho Ko Kenji Kawaguchi Juho Lee Sung Ju Hwang DD 52 3 0 10 Oct 2023
Dataset Condensation via Generative Model David Junhao Zhang Heng Wang Chuhui Xue Rui Yan Wenqing Zhang Song Bai Mike Zheng Shou DD 26 11 0 14 Sep 2023
Vision-Language Dataset Distillation Xindi Wu Byron Zhang Zhiwei Deng Olga Russakovsky DD VLM 33 8 0 15 Aug 2023
Rethinking Data Distillation: Do Not Overlook Calibration Dongyao Zhu Bowen Lei Jie M. Zhang Yanbo Fang Ruqi Zhang Yiqun Xie Dongkuan Xu DD FedML 23 15 0 24 Jul 2023
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning Zhenyi Wang Enneng Yang Li Shen Heng-Chiao Huang KELM MU 34 48 0 16 Jul 2023
The Importance of Robust Features in Mitigating Catastrophic Forgetting Hikmat Khan N. Bouaynaya Ghulam Rasool 27 7 0 29 Jun 2023
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective Zeyuan Yin Eric P. Xing Zhiqiang Shen DD 20 63 0 22 Jun 2023
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data Xin Zheng Miao Zhang C. Chen Quoc Viet Hung Nguyen Xingquan Zhu Shirui Pan DD 41 59 0 05 Jun 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
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 59 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 93 84 0 02 May 2023
Bayesian Pseudo-Coresets via Contrastive Divergence Piyush Tiwary Kumar Shubham V. Kashyap Prathosh A.P. 21 3 0 20 Mar 2023
DiM: Distilling Dataset into Generative Model Kai Wang Jianyang Gu Daquan Zhou Zheng Hua Zhu Wei Jiang Yang You DD 56 40 0 08 Mar 2023
EcoTTA: Memory-Efficient Continual Test-time Adaptation via Self-distilled Regularization Jun S. Song Jungsoo Lee In So Kweon Sungha Choi TTA 36 83 0 03 Mar 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
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory Justin Cui Ruochen Wang Si Si Cho-Jui Hsieh DD 25 129 0 19 Nov 2022
Kernel Continual Learning Mohammad Mahdi Derakhshani Xiantong Zhen Ling Shao Cees G. M. Snoek CLL BDL VLM 70 38 0 12 Jul 2021
Pragmatic Image Compression for Human-in-the-Loop Decision-Making S. Reddy Anca Dragan Sergey Levine OffRL 44 13 0 07 Jul 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 199 288 0 16 Feb 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 127 406 0 06 Mar 2017