Search Results for author: Zeyi Huang

Found 15 papers, 11 papers with code

Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation

1 code implementation4 Jun 2022 Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing

Finally, we test this simple technique we identify (worst-case data augmentation with squared l2 norm alignment regularization) and show that the benefits of this method outrun those of the specially designed methods.

Data Augmentation

The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization

1 code implementation9 Apr 2022 Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing

Training with an emphasis on "hard-to-learn" components of the data has been proven as an effective method to improve the generalization of machine learning models, especially in the settings where robustness (e. g., generalization across distributions) is valued.

BIG-bench Machine Learning Domain Generalization

The Two Dimensions of Worst-Case Training and Their Integrated Effect for Out-of-Domain Generalization

no code implementations CVPR 2022 Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing

Training with an emphasis on "hard-to-learn" components of the data has been proven as an effective method to improve the generalization of machine learning models, especially in the settings where robustness (e. g., generalization across distributions) is valued.

BIG-bench Machine Learning Domain Generalization

On the Integration of Self-Attention and Convolution

1 code implementation CVPR 2022 Xuran Pan, Chunjiang Ge, Rui Lu, Shiji Song, Guanfu Chen, Zeyi Huang, Gao Huang

In this paper, we show that there exists a strong underlying relation between them, in the sense that the bulk of computations of these two paradigms are in fact done with the same operation.

Representation Learning

Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features

1 code implementation5 Nov 2021 Haohan Wang, Zeyi Huang, HANLIN ZHANG, Yong Jae Lee, Eric Xing

Machine learning has demonstrated remarkable prediction accuracy over i. i. d data, but the accuracy often drops when tested with data from another distribution.

BIG-bench Machine Learning

Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image Recognition

2 code implementations NeurIPS 2021 Yulin Wang, Rui Huang, Shiji Song, Zeyi Huang, Gao Huang

Inspired by this phenomenon, we propose a Dynamic Transformer to automatically configure a proper number of tokens for each input image.

Ranked #27 on Image Classification on CIFAR-100 (using extra training data)

Image Classification

Learning Robust Models by Countering Spurious Correlations

no code implementations1 Jan 2021 Haohan Wang, Zeyi Huang, Eric Xing

In this paper, we formally study the generalization error bound for this setup with the knowledge of how the spurious features are associated with the label.

Domain Adaptation

On the Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations

no code implementations1 Jan 2021 Haohan Wang, Zeyi Huang, Xindi Wu, Eric Xing

Data augmentation is one of the most popular techniques for improving the robustness of neural networks.

Data Augmentation

Self-Challenging Improves Cross-Domain Generalization

7 code implementations ECCV 2020 Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang

We introduce a simple training heuristic, Representation Self-Challenging (RSC), that significantly improves the generalization of CNN to the out-of-domain data.

Domain Generalization Image Classification

Multiple Anchor Learning for Visual Object Detection

3 code implementations CVPR 2020 Wei Ke, Tianliang Zhang, Zeyi Huang, Qixiang Ye, Jianzhuang Liu, Dong Huang

In this paper, we propose a Multiple Instance Learning (MIL) approach that selects anchors and jointly optimizes the two modules of a CNN-based object detector.

Ranked #92 on Object Detection on COCO test-dev (using extra training data)

General Classification Multiple Instance Learning +2

High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

1 code implementation28 May 2019 Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing

We investigate the relationship between the frequency spectrum of image data and the generalization behavior of convolutional neural networks (CNN).

Adversarial Attack

Improving Object Detection with Inverted Attention

1 code implementation28 Mar 2019 Zeyi Huang, Wei Ke, Dong Huang

Our approach (1) operates along both the spatial and channels dimensions of the feature maps; (2) requires no extra training on hard samples, no extra network parameters for attention estimation, and no testing overheads.

object-detection Object Detection

Large Margin Object Tracking with Circulant Feature Maps

no code implementations CVPR 2017 Mengmeng Wang, Yong liu, Zeyi Huang

Structured output support vector machine (SVM) based tracking algorithms have shown favorable performance recently.

Object Tracking

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