Search Results for author: Yidong Wang

Found 12 papers, 7 papers with code

SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

1 code implementation26 Jan 2023 Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Bhiksha Raj, Marios Savvides

The critical challenge of Semi-Supervised Learning (SSL) is how to effectively leverage the limited labeled data and massive unlabeled data to improve the model's generalization performance.

imbalanced classification

An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning

no code implementations20 Nov 2022 Hao Chen, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Marios Savvides, Bhiksha Raj

While standard SSL assumes uniform data distribution, we consider a more realistic and challenging setting called imbalanced SSL, where imbalanced class distributions occur in both labeled and unlabeled data.

Pseudo Label

GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective

1 code implementation15 Nov 2022 Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, Jindong Wang, Xing Xie, Yue Zhang

Pre-trained language models (PLMs) are known to improve the generalization performance of natural language understanding models by leveraging large amounts of data during the pre-training phase.

Natural Language Understanding Out-of-Distribution Generalization

Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution

no code implementations1 Sep 2022 Wang Lu, Jindong Wang, Yidong Wang, Kan Ren, Yiqiang Chen, Xing Xie

For optimization, we utilize an adapted Mixup to generate an out-of-distribution dataset that can guide the preference direction and optimize with Pareto optimization.

Domain Generalization Model Optimization +1

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets

no code implementations15 Aug 2022 Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, Marios Savvides

Beyond classification, Conv-Adapter can generalize to detection and segmentation tasks with more than 50% reduction of parameters but comparable performance to the traditional full fine-tuning.

Transfer Learning

Margin Calibration for Long-Tailed Visual Recognition

no code implementations14 Dec 2021 Yidong Wang, BoWen Zhang, Wenxin Hou, Zhen Wu, Jindong Wang, Takahiro Shinozaki

The long-tailed class distribution in visual recognition tasks poses great challenges for neural networks on how to handle the biased predictions between head and tail classes, i. e., the model tends to classify tail classes as head classes.

FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling

1 code implementation NeurIPS 2021 BoWen Zhang, Yidong Wang, Wenxin Hou, Hao Wu, Jindong Wang, Manabu Okumura, Takahiro Shinozaki

However, like other modern SSL algorithms, FixMatch uses a pre-defined constant threshold for all classes to select unlabeled data that contribute to the training, thus failing to consider different learning status and learning difficulties of different classes.

Semi-Supervised Image Classification

Exploiting Adapters for Cross-lingual Low-resource Speech Recognition

2 code implementations18 May 2021 Wenxin Hou, Han Zhu, Yidong Wang, Jindong Wang, Tao Qin, Renjun Xu, Takahiro Shinozaki

Based on our previous MetaAdapter that implicitly leverages adapters, we propose a novel algorithms called SimAdapter for explicitly learning knowledge from adapters.

Cross-Lingual ASR General Knowledge +3

Unsupervised segmentation via semantic-apparent feature fusion

no code implementations21 May 2020 Xi Li, Huimin Ma, Hongbing Ma, Yidong Wang

In order to solve this problem, the research proposes an unsupervised foreground segmentation method based on semantic-apparent feature fusion (SAFF).

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