Loss-Curvature Matching for Dataset Selection and Condensation

8 March 2023

Papers citing "Loss-Curvature Matching for Dataset Selection and Condensation"

8 / 8 papers shown

Title
Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios Kai Wang Zekai Li Zhi-Qi Cheng Samir Khaki A. Sajedi Ramakrishna Vedantam Konstantinos N. Plataniotis Alexander G. Hauptmann Yang You DD 54 4 0 22 Oct 2024
Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator Xin Zhang Jiawei Du Ping Liu Joey Tianyi Zhou DD 42 2 0 13 Aug 2024
Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching Tao Feng Jie Zhang Peizheng Wang Zhijie Wang Shengyuan Pang DD 38 0 0 29 May 2023
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 375 155 0 30 May 2022
Carbon Emissions and Large Neural Network Training David A. Patterson Joseph E. Gonzalez Quoc V. Le Chen Liang Lluís-Miquel Munguía D. Rothchild David R. So Maud Texier J. Dean AI4CE 233 626 0 21 Apr 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training Krishnateja Killamsetty D. Sivasubramanian Ganesh Ramakrishnan A. De Rishabh K. Iyer OOD 73 184 0 27 Feb 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 183 219 0 16 Feb 2021
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 236 35,884 0 25 Aug 2016