Dataset condensation with contrastive signals
WebTo address this problem, we propose Dataset Condensation with Contrastive signals (DCC) by modifying the loss function to enable the DC methods to effectively capture the … WebSep 12, 2024 · In this work, we analyse the contrastive fine-tuning of pre-trained language models on two fine-grained text classification tasks, emotion classification and sentiment analysis. We adaptively embed class relationships into a contrastive objective function to help differently weigh the positives and negatives, and in particular, weighting ...
Dataset condensation with contrastive signals
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WebTo address this problem, we propose Dataset Condensation with Contrastive signals (DCC) by modifying the loss function to enable the DC methods to effectively capture the differences between classes. In addition, we analyze the new loss function in terms of training dynamics by tracking the kernel velocity. WebFigure 1: Dataset Condensation (left) aims to generate a small set of synthetic images that can match the performance of a network trained on a large image dataset. Our method (right) realizes this goal by learning a synthetic set such that a deep network trained on it and the large set produces similar gradients w.r.t. its weights.
WebDataset Condensation With Contrastive Signals relevant information (e.g., logo, police sign, trailers) while suppressing task-irrelevant information (e.g., wheels, head … Web[24]Saehyung Lee, Sanghyuk Chun, Sangwon Jung, Sangdoo Yun, Sungroh Yoon, \Dataset Condensation with Contrastive Signals", International Conference on Machine Learning (ICML), 2024. ... IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024 [7]Sangdoo Yun, Dongyoon Han, Seong Joon Oh, …
Weboverlooking contrastive signals. •To address this issue, we propose the Dataset Condensation with Contrastive signals (DCC) method. •In our experiments, we … WebConclusion •We show that DC primarily focuses on the class-wise gradient while overlooking contrastive signals. •To address this issue, we propose the Dataset Condensation with Contrastive signals (DCC) method. •In our experiments, we demonstrate that the proposed DCC outperforms DC in fine-grained classification tasks and general benchmark datasets
WebProceedings of Machine Learning Research
WebFeb 7, 2024 · To address this problem, we propose Dataset Condensation with Contrastive signals (DCC) by modifying the loss function to enable the DC methods to … curly weave beauty supplyWebSpotlight 08:20 Dataset Condensation via Efficient Synthetic-Data Parameterization. ... Spotlight 08:35 Dataset Condensation with Contrastive Signals. Saehyung Lee · Sanghyuk Chun · Sangwon Jung · Sangdoo Yun · Sungroh Yoon. Poster 15:00 Blurs Behave Like Ensembles: ... curly wavy hair with curtain bangsWebJul 24, 2024 · Online Continual Learning with Contrastive Vision Transformer. Online continual learning (online CL) studies the problem of learning sequential tasks from an … curly wavy hairstyles medium hairWebFeb 7, 2024 · This study proposes Dataset Condensation with Contrastive signals (DCC) by modifying the loss function to enable the DC methods to effectively capture the … curly wavy hairstylesWebDataset Condensation with Contrastive Signals. Contribute to Daankrol/DCC development by creating an account on GitHub. curly wavy human hair weaveWebRecent studies on dataset condensation attempt to reduce the dependence on such massive data by synthesizing a compact training dataset. However, the existing … curly wavy hair typesWebTo address this problem, we propose Dataset Condensation with Contrastive signals (DCC) by modifying the loss function to enable the DC methods to effectively capture the differences between classes. In addition, we analyze the new loss function in terms of training dynamics by tracking the kernel velocity. Furthermore, we introduce a bi-level ... curly wavy hairstyles for women over 50