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08/12/2023
Semantic Equivariant Mixup
Mixup is a well-established data augmentation technique, which can exten...
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06/03/2023
Provable Dynamic Fusion for Low-Quality Multimodal Data
The inherent challenge of multimodal fusion is to precisely capture the ...
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06/02/2023
dugMatting: Decomposed-Uncertainty-Guided Matting
Cutting out an object and estimating its opacity mask, known as image ma...
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06/02/2023
Calibrating Multimodal Learning
Multimodal machine learning has achieved remarkable progress in a wide r...
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05/22/2023
Semantic Invariant Multi-view Clustering with Fully Incomplete Information
Robust multi-view learning with incomplete information has received sign...
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04/11/2023
Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification
Classifying incomplete multi-view data is inevitable since arbitrary vie...
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04/09/2023
Reweighted Mixup for Subpopulation Shift
Subpopulation shift exists widely in many real-world applications, which...
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03/23/2023
Fairness-guided Few-shot Prompting for Large Language Models
Large language models have demonstrated surprising ability to perform in...
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02/14/2023
Balanced Audiovisual Dataset for Imbalance Analysis
The imbalance problem is widespread in the field of machine learning, wh...
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12/08/2022
Graph Matching with Bi-level Noisy Correspondence
In this paper, we study a novel and widely existing problem in graph mat...
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09/19/2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup
Subpopulation shift wildly exists in many real-world machine learning ap...
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04/25/2022
Trusted Multi-View Classification with Dynamic Evidential Fusion
Existing multi-view classification algorithms focus on promoting accurac...
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01/15/2022
Uncertainty-Aware Multi-View Representation Learning
Learning from different data views by exploring the underlying complemen...
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11/17/2021
Trustworthy Long-Tailed Classification
Classification on long-tailed distributed data is a challenging problem,...
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11/11/2021
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Multimodal regression is a fundamental task, which integrates the inform...
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10/15/2021
Identifying Incorrect Classifications with Balanced Uncertainty
Uncertainty estimation is critical for cost-sensitive deep-learning appl...
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02/03/2021
Trusted Multi-View Classification
Multi-view classification (MVC) generally focuses on improving classific...
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11/12/2020
Deep Partial Multi-View Learning
Although multi-view learning has made signifificant progress over the pa...
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10/31/2020
LRA: an accelerated rough set framework based on local redundancy of attribute for feature selection
In this paper, we propose and prove the theorem regarding the stability ...
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08/16/2020
SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning
Although significant progress achieved, multi-label classification is st...
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05/06/2020
Diagnosis of Coronavirus Disease 2019 (COVID-19) with Structured Latent Multi-View Representation Learning
Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread...
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05/02/2020
Ball k-means
This paper presents a novel accelerated exact k-means algorithm called t...
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08/06/2019
Multi-view Deep Subspace Clustering Networks
Multi-view subspace clustering aims to discover the inherent structure b...
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05/12/2019
Deep Vocoder: Low Bit Rate Compression of Speech with Deep Autoencoder
Inspired by the success of deep neural networks (DNNs) in speech process...
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05/12/2019
Deep Vocoder: Low Bit Rate Speech Compression of Speech with Deep Autoencoder
Inspired by the success of deep neural networks (DNNs) in speech process...
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12/11/2018
Unsupervised Degradation Learning for Single Image Super-Resolution
Deep Convolution Neural Networks (CNN) have achieved significant perform...
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05/19/2018
Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image
Glaucoma is a chronic eye disease that leads to irreversible vision loss...
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10/14/2017
