Data pruning and neural scaling laws: fundamental limitations of score-based algorithms

14 February 2023

Papers citing "Data pruning and neural scaling laws: fundamental limitations of score-based algorithms"

6 / 6 papers shown

Title
Efficient Alignment of Large Language Models via Data Sampling Amrit Khera Rajat Ghosh Debojyoti Dutta 36 1 0 15 Nov 2024
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
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 45 73 0 11 Jan 2023
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 88 188 0 27 Feb 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 196 288 0 16 Feb 2021
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 234 4,469 0 23 Jan 2020