Robust Domain Adaptation

Robust domain adaptation aims to train machine learning models that generalize well to new, unseen data distributions, overcoming the limitations of traditional models which struggle with data heterogeneity. Current research focuses on improving model robustness through techniques like adversarial training, data augmentation (including adversarial and random transformations), and optimal transport methods to align source and target domain distributions, often within unsupervised or semi-supervised learning frameworks. These advancements are crucial for deploying machine learning models in real-world applications where data scarcity or shifts in distribution are common, particularly in fields like medical imaging and natural language processing.

Papers

May 15, 2024

AD-Aligning: Emulating Human-like Generalization for Cognitive Domain Adaptation in Deep Learning
Zhuoying Li, Bohua Wan, Cong Mu, Ruzhang Zhao, Shushan Qiu, Chao Yan
Deep Learning Domain Adaptation Domain Adaptation Task Human Like Generalization Robust Domain Adaptation Source Target Domain Ad Placement

October 25, 2023

Robust Source-Free Domain Adaptation for Fundus Image Segmentation
Lingrui Li, Yanfeng Zhou, Ge Yang
Domain Adaptation Medical Image Segmentation Segmentation Model Source Free Domain Adaptation Fundus Image Segmentation Robust Domain Adaptation

October 18, 2023

CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation
Philipp Borchert, Jochen De Weerdt, Kristof Coussement, Arno De Caigny, Marie-Francine Moens
Domain Adaptation Complex ECC Core Relation Comprehension Relation Information Robust Domain Adaptation Shot Relation Word Relation

August 8, 2023

Data Augmentation-Based Unsupervised Domain Adaptation In Medical Imaging
Sebastian Nørgaard Llambias, Mads Nielsen, Mostafa Mehdipour Ghazi
Domain Adaptation Data Augmentation Raw Data Domain Shift Medical Imaging Unsupervised Method Brain Segmentation Robust Domain Adaptation

April 17, 2023

Implicit Bayes Adaptation: A Collaborative Transport Approach
Bo Jiang, Hamid Krim, Tianfu Wu, Derya Cansever
Domain Adaptation Optimal Transport Unsupervised Domain Adaptation Structural Prior Cooperative Transportation Robust Domain Adaptation

March 30, 2023

CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation
Wenqiao Zhang, Changshuo Liu, Can Cui, Beng Chin Ooi
Domain Adaptation Causal Event Semi Supervised Domain Adaptation Cross Domain Feature Alignment Robust Domain Adaptation Proxy Task

February 23, 2023

On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space
Yuyang Deng, Nidham Gazagnadou, Junyuan Hong, Mehrdad Mahdavi, Lingjuan Lyu
Visual Perspective Hardness Result Cross Domain Generalization Rademacher Complexity Hypothesis Space Robustness Transfer Robust Domain Adaptation

November 13, 2022

Adversarial and Random Transformations for Robust Domain Adaptation and Generalization
Liang Xiao, Jiaolong Xu, Dawei Zhao, Erke Shang, Qi Zhu, Bin Dai
Data Augmentation Strong Generalization Adversarial Example Adversarial Text Adversarial Augmentation Random Transformation Adversarial Data Augmentation Robust Domain Adaptation Random Data Augmentation

October 30, 2022

Distributionally Robust Domain Adaptation
Akram S. Awad, George K. Atia
Domain Adaptation Domain Distribution Robust Domain Adaptation High Risk Domain

October 26, 2022

Robust Domain Adaptation for Pre-trained Multilingual Neural Machine Translation Models
Mathieu Grosso, Pirashanth Ratnamogan, Alexis Mathey, William Vanhuffel, Michael Fotso Fotso
Domain Adaptation Language Pair Multilingual Neural Machine Translation Pre Trained Neural Machine Translation Robust Domain Adaptation Pre Trained Multilingual

September 23, 2022

Robust Domain Adaptation for Machine Reading Comprehension
Liang Jiang, Zhenyu Huang, Jia Liu, Zujie Wen, Xi Peng
Domain Adaptation Machine Reading Comprehension Novel Domain Adaptation Robust Domain Adaptation

Robust Domain Adaptation

Papers

AD-Aligning: Emulating Human-like Generalization for Cognitive Domain Adaptation in Deep Learning

Robust Source-Free Domain Adaptation for Fundus Image Segmentation

CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation

Data Augmentation-Based Unsupervised Domain Adaptation In Medical Imaging

Implicit Bayes Adaptation: A Collaborative Transport Approach

CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation

On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space

Adversarial and Random Transformations for Robust Domain Adaptation and Generalization

Distributionally Robust Domain Adaptation

Robust Domain Adaptation for Pre-trained Multilingual Neural Machine Translation Models

Robust Domain Adaptation for Machine Reading Comprehension