Dataset distillation: a survey
WebA Comprehensive Survey to Dataset Distillation. Author(s): Shiye Lei ... Dataset distillation, one of the dataset reduction methods, tackles the problem via synthesising a small typical dataset from giant data and has attracted a lot of attention from the deep learning community. Existing dataset distillation methods can be taxonomised into ... WebJan 13, 2024 · To this end, diverse approaches are proposed to improve data processing efficiency. Dataset distillation, one of the dataset reduction methods, tackles the problem via synthesising a small...
Dataset distillation: a survey
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WebJul 22, 2024 · Abstract: Dataset distillation is a method for reducing dataset sizes by learning a small number of representative synthetic samples. This has several benefits such as speeding up model training, reducing energy consumption, and reducing required storage space. These benefits are especially crucial in settings like federated learning where … WebFeb 27, 2024 · Unlike the model distillation method, this architecture uses the dataset distillation method, in which the client distills the local data and uploads the synthetic data and learning rate to the server. The server combines the synthetic data from the users to train a global model. ... Liu, S.; Jin, Y. Federated learning on non-IID data: A survey ...
WebJan 13, 2024 · improve data processing efficiency. Dataset distillation, one of the dataset reduction methods, tackles the problem via synthesising a small typical dataset from giant data and has attracted a lot of attention from the deep learning community. Existing dataset distillation methods can be taxonomised into WebJan 11, 2024 · As an alternative, data distillation approaches aim to synthesize terse data summaries, which can serve as effective drop-in replacements of the original dataset for …
WebDataset distillation aims to generate a small informative dataset such that the models trained on these samples have similar test performance to those trained on the original dataset. ... 知识蒸馏 综述 Knowledge Distillation: A Survey. 综述：Recent Advances in Features Extraction and Description Algorithms: A Comprehensive Survey WebJan 11, 2024 · Data Distillation: A Survey Noveen Sachdeva, Julian McAuley Published 11 January 2024 Computer Science ArXiv The popularity of deep learning has led to the …
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WebJan 13, 2024 · A Comprehensive Survey to Dataset Distillation Shiye Lei, Dacheng Tao Published 13 January 2024 Computer Science ArXiv Deep learning technology has … marly pitscWebDec 15, 2024 · Dataset distillation can be formulated as a two-stage optimization process: an “inner loop” that trains a model on learned data, and an “outer loop” that optimizes the … marly plantersWebMar 15, 2024 · The knowledge distillation (KD) technology proposed in 2015 was first applied to image classification in the field of computer vision, and quickly expanded to other visual tasks. The reason for this may be that the complex teacher models can transfer knowledge (learned from large-scale data or other multi-modal data) to lightweight … marlyplastWebThe popularity of deep learning has led to the curation of a vast number of massive and multifarious datasets. Despite having close-to-human performance on individual tasks, … nbc26.com green bayWebSep 5, 2024 · The dataset distillation technique effectively compresses the entire dataset, but the compression loss increases for datasets with high-dimensional features. The experiments in this study are conducted on a dataset with a test accuracy of at least 50% using distilled images, under the assumption that the dataset distillation guaranties a ... nbc26.com weatherWebJan 13, 2024 · 01/13/23 - Deep learning technology has unprecedentedly developed in the last decade and has become the primary choice in many application do... marly pluiWebNov 2, 2024 · Within each category, we further divide knowledge distillation methods into two subcategories: (1) offline distillation and (2) online distillation. A summary can be found in Fig. 3. In this survey, our main criteria are change in sizes and accuracy scores of student models against the corresponding teacher models. nbc 25 weather