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Prototypical Classifier for Robust Class-Imbalanced Learning

https://doi.org/10.1007/978-3-031-05936-0_4

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4899-7687-1_79openalex-snapshot

Empirical Risk Minimization

inferredcites →https://doi.org/10.1007/978-3-319-46478-7_29openalex-snapshot

Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2019.00264openalex-snapshot

Large-Scale Long-Tailed Recognition in an Open World

inferredcites →https://doi.org/10.1109/cvpr.2019.00949openalex-snapshot

Class-Balanced Loss Based on Effective Number of Samples

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00763openalex-snapshot

Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition From a Domain Adaptation Perspective

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00974openalex-snapshot

BBN: Bilateral-Branch Network With Cumulative Learning for Long-Tailed Visual Recognition

inferredcites →https://doi.org/10.1109/iccv48922.2021.00013openalex-snapshot

NGC: A Unified Framework for Learning with Open-World Noisy Data

inferredcites →https://doi.org/10.1109/iccv48922.2021.00935openalex-snapshot

Learning from Noisy Data with Robust Representation Learning

inferredcites →https://doi.org/10.1109/tnnls.2019.2935143openalex-snapshot

Does Tail Label Help for Large-Scale Multi-Label Learning?

inferredcites →https://doi.org/10.1109/tpami.2013.83openalex-snapshot

Distance-Based Image Classification: Generalizing to New Classes at Near-Zero Cost

inferredcites →https://doi.org/10.48550/arxiv.1703.05175openalex-snapshot

Prototypical Networks for Few-shot Learning

inferredcites →https://doi.org/10.48550/arxiv.1708.02862openalex-snapshot

WebVision Database: Visual Learning and Understanding from Web Data

inferredcites →https://doi.org/10.48550/arxiv.1710.09412openalex-snapshot

mixup: Beyond Empirical Risk Minimization

inferredcites →https://doi.org/10.48550/arxiv.1803.09050openalex-snapshot

Learning to Reweight Examples for Robust Deep Learning

inferredcites →https://doi.org/10.48550/arxiv.1804.06872openalex-snapshot

Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

inferredcites →https://doi.org/10.48550/arxiv.1902.07379openalex-snapshot

Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting

inferredcites →https://doi.org/10.48550/arxiv.1910.09217openalex-snapshot

Decoupling Representation and Classifier for Long-Tailed Recognition

inferredcites →https://doi.org/10.48550/arxiv.2002.07394openalex-snapshot

DivideMix: Learning with Noisy Labels as Semi-supervised Learning

inferredcites →https://doi.org/10.48550/arxiv.2006.15766openalex-snapshot

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization

inferredcites →https://doi.org/10.48550/arxiv.2007.10740openalex-snapshot

Balanced Meta-Softmax for Long-Tailed Visual Recognition

inferredcites →https://doi.org/10.48550/arxiv.2009.07995openalex-snapshot

MoPro: Webly Supervised Learning with Momentum Prototypes

inferredcites →https://doi.org/10.48550/arxiv.2108.11096openalex-snapshot

Learning From Long-Tailed Data With Noisy Labels

inferredcites →https://doi.org/10.48550/arxiv.2108.11569openalex-snapshot

Robust Long-Tailed Learning under Label Noise

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-05933-9openalex-snapshot

Advances in Knowledge Discovery and Data Mining

inferred← citeshttps://doi.org/10.1007/978-3-031-05936-0openalex-snapshot

Advances in Knowledge Discovery and Data Mining

inferred← citeshttps://doi.org/10.1007/978-3-031-72630-9_10openalex-snapshot

Distribution-Aware Robust Learning from Long-Tailed Data with Noisy Labels

inferred← citeshttps://doi.org/10.1007/978-981-19-8746-5_8openalex-snapshot

Effective Imbalance Learning Utilizing Informative Data

inferred← citeshttps://doi.org/10.1007/s10994-022-06247-zopenalex-snapshot

Transfer and share: semi-supervised learning from long-tailed data

inferred← citeshttps://doi.org/10.1007/s11704-023-3200-zopenalex-snapshot

Rts: learning robustly from time series data with noisy label

inferred← citeshttps://doi.org/10.1007/s11760-024-03525-2openalex-snapshot

A federated learning method based on class prototype guided classifier for long-tailed data

inferred← citeshttps://doi.org/10.1109/access.2024.3418669openalex-snapshot

Ant-Based Feature and Instance Selection for Multiclass Imbalanced Data

inferred← citeshttps://doi.org/10.1109/cvpr52729.2023.01496openalex-snapshot

Towards Effective Visual Representations for Partial-Label Learning

inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3546031openalex-snapshot

Prototype-Oriented Clean Subset Extraction for Noisy Long-Tailed Classification

inferred← citeshttps://doi.org/10.1145/3624918.3625318openalex-snapshot

Automatic Feature Fairness in Recommendation via Adversaries

inferred← citeshttps://doi.org/10.1609/aaai.v37i6.25927openalex-snapshot

Long-Tail Cross Modal Hashing

inferred← citeshttps://doi.org/10.1609/aaai.v38i14.29532openalex-snapshot

A Separation and Alignment Framework for Black-Box Domain Adaptation

inferred← citeshttps://doi.org/10.24963/ijcai.2023/434openalex-snapshot

Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels

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