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Joint Cross-Domain and Cross-Lingual Adaptation for Chinese Opinion Element Extraction
Opinion element extraction, through which key elements of opinions are identified, is critical for understanding opinions. We can achieve...
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Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation
This paper studies a new, practical but challenging problem, called Class-Incremental Unsupervised Domain Adaptation (CI-UDA), where the labeled...
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Domain Adaptation with Maximum Margin Criterion with Application to Network Traffic Classification
A fundamental assumption in machine learning is that training and test samples follow the same distribution. Therefore, for training a machine...
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A novel hierarchical attention-based triplet network with unsupervised domain adaptation for network intrusion detection
Network Intrusion Detection Systems(NIDSs) are crucial for resisting cyber threats. However, NIDSs equipped with supervised learning models do not...
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Universal Domain Adaptation
Domain adaptation with strict assumptions on the label set relations is extensively explored both in previous chapters and in the literature. These...
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Universal Object Detection with Large Vision Model
Over the past few years, there has been growing interest in develo** a broad, universal, and general-purpose computer vision system. Such systems...
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Adversarial Partial Domain Adaptation by Cycle Inconsistency
Unsupervised partial domain adaptation (PDA) is a unsupervised domain adaptation problem which assumes that the source label space subsumes the...
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A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
Domain Adaptation (DA) is a technique that aims at extracting information from a labeled remote sensing image to allow classifying a different image...
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LIMFA: label-irrelevant multi-domain feature alignment-based fake news detection for unseen domain
Fake news in social networks causes disastrous effects on the real world yet effectively detecting newly emerged fake news remains difficult. This...
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Multi-source-free Domain Adaptive Object Detection
To enhance the transferability of object detection models in real-world scenarios where data is sampled from disparate distributions, considerable...
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Source-Free Unsupervised Domain Adaptation with Sample Transport Learning
Unsupervised domain adaptation (UDA) has achieved great success in handling cross-domain machine learning applications. It typically benefits the...
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Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
The prime challenge in unsupervised domain adaptation (DA) is to mitigate the domain shift between the source and target domains. Prior DA works show...
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Multi-source Information-Shared Domain Adaptation for EEG Emotion Recognition
EEG-based affective computing aims to provide an objective method to evaluate people’s emotional states in human-computer interactions, but it...
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A Broad Study of Pre-training for Domain Generalization and Adaptation
Deep models must learn robust and transferable representations in order to perform well on new domains. While domain transfer methods (e.g., domain...
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Feature extractor stacking for cross-domain few-shot learning
Cross-domain few-shot learning (CDFSL) addresses learning problems where knowledge needs to be transferred from one or more source domains into an...
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MemSAC: Memory Augmented Sample Consistency for Large Scale Domain Adaptation
Practical real world datasets with plentiful categories introduce new challenges for unsupervised domain adaptation like small inter-class...
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Domain Adaptation of Transformer-Based Models Using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback
Understanding customer feedback is becoming a necessity for companies to identify problems and improve their products and services. Text...
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Principles of Universal Conceptual Modeling
The paper proposes a new frontier for conceptual modeling – universal conceptual modeling (UCM) – defined as conceptual modeling that is...
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From Universal Design to Attainable Game Experiences
Video games constitute an important part of peoples’ lives, both from an entertainment perspective and for purposes that go beyond entertainment. For...
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Exploring the Impact of Various Contrastive Learning Loss Functions on Unsupervised Domain Adaptation in Person Re-identification
Person Re-identification has drawn great attention in the industrial surveillance system. This paper focuses on the unsupervised domain adaptive case...