Dataset condensation with contrastive signals

Author: icbv

August undefined, 2024

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 effectively capture the differences between classes. In addition, we analyze the new loss function in terms of training dynamics by tracking the kernel velocity. WebCurrently, he works as the head of NAVER AI Lab in NAVER Cloud. He has contributed to the AI research community as Datasets and Benchmarks Co-chair for NeurIPS and Social Co-chair for ICML 2024 and NeurIPS 2024. Also, he has joined a senior technical program committee member, such as, Area chair for NeurIPS 2024 and 2024, Area chair for ICML ...

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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, … WebSep 28, 2024 · This paper proposes a training set synthesis technique for data-efficient learning, called Dataset Condensation, that learns to condense large dataset into a … how to say sizes in spanish

Sanghyuk Chun

WebProceedings of Machine Learning Research WebApr 15, 2024 · Condensing Graphs via One-Step Gradient Matching. However, existing approaches have their inherent limitations: (1) they are not directly applicable to … WebDataset Condensation with Contrastive Signals. Contribute to Daankrol/DCC development by creating an account on GitHub. how to say sixty five in spanish

Dataset Condensation with Contrastive Signals - icml.cc

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 http://proceedings.mlr.press/v139/zhao21a/zhao21a.pdf how to say sixty three in spanishWebTo 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 … northland pines high school basketball

"WebNon-Contrastive Unsupervised Learning of Physiological Signals from Video Jeremy Speth · Nathan Vance · Patrick Flynn · Adam Czajka High-resolution image reconstruction with latent diffusion models from human brain activity Yu Takagi · Shinji Nishimoto RIFormer: Keep Your Vision Backbone Effective But Removing Token Mixer " - Dataset condensation with contrastive signals

Dataset condensation with contrastive signals

WebDataset Condensation with Contrastive Signals Recent studies have demonstrated that gradient matching-based dataset sy... 0 Saehyung Lee, et al. ∙ share research ∙ 2 years ago Removing Undesirable Feature Contributions Using Out-of-Distribution Data Several data augmentation methods deploy unlabeled-in-distribution (UID)... 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.

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WebDataset Condensation with Contrastive Signals (Saehyung Lee et al., ICML 2024) 📖 Delving into Effective Gradient Matching for Dataset Condensation (Zixuan Jiang et al., 2024) 📖 Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory (Justin Cui et … WebDataset Condensation With Contrastive Signals lights, roads, trees). In our experiments on the ﬁne-grained Automobile dataset, DC results in a classiﬁer with a test accuracy (11%) lower than that achieved using the random selection method (12.2%). We demonstrate that DC cannot effectively utilize the contrastive signals of interclass sam-

WebTitle: Dataset Condensation with Contrastive Signals Authors: Saehyung Lee, Sanghyuk Chun, Sangwon Jung, Sangdoo Yun, Sungroh Yoon Abstract summary: gradient … WebDataset Condensation With Contrastive Signals relevant information (e.g., logo, police sign, trailers) while suppressing task-irrelevant information (e.g., wheels, head …

WebSpotlight 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: ...

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WebAug 10, 2016 · In light of current global climate change forecasts, there is an urgent need to better understand how reef-building corals respond to changes in temperature. Multivariate statistical approaches (MSA), including principal components analysis and multidimensional scaling, were used herein to attempt to understand the response of the common, Indo … how to say skateboard in spanishWebFeb 7, 2024 · Dataset Condensation with Contrastive Signals. Recent studies have demonstrated that gradient matching-based dataset synthesis, or dataset condensation … how to say size in frenchWebFeb 7, 2024 · Algorithm 1 Dataset condensation with contrastive signals. Figure 4 shows the NTK velocity during synthetic dataset optimization using DC and DCC on CIFAR-10. As … northland pines high school hockey scheduleWeboverlooking contrastive signals. •To address this issue, we propose the Dataset Condensation with Contrastive signals (DCC) method. •In our experiments, we … how to say sixth in italianWebFeb 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 … northland pines fitness centerWebJul 24, 2024 · Online Continual Learning with Contrastive Vision Transformer. Online continual learning (online CL) studies the problem of learning sequential tasks from an … northland pines eagle river wi parent portalWebJan 29, 2024 · Photo by AJ Jean on Unsplash. The topic of data-efficient learning an important topic in Data Science and is an active area of research. Training large models … northland pines high school sports