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09/21/2023
Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning
In open-world semi-supervised learning, a machine learning model is task...
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08/31/2023
Robust Representation Learning for Unreliable Partial Label Learning
Partial Label Learning (PLL) is a type of weakly supervised learning whe...
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06/15/2023
Partial-Label Regression
Partial-label learning is a popular weakly supervised learning setting t...
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05/26/2023
Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
In many real-world tasks, the concerned objects can be represented as a ...
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05/17/2023
Complementary Classifier Induced Partial Label Learning
In partial label learning (PLL), each training sample is associated with...
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05/10/2023
Rethinking the Value of Labels for Instance-Dependent Label Noise Learning
Label noise widely exists in large-scale datasets and significantly dege...
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03/27/2023
Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection
Weakly Supervised Object Detection (WSOD) enables the training of object...
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02/25/2023
Complementary to Multiple Labels: A Correlation-Aware Correction Approach
Complementary label learning (CLL) requires annotators to give irrelevan...
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12/18/2022
Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision
Weakly supervised machine learning algorithms are able to learn from amb...
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10/08/2022
A Survey on Extreme Multi-label Learning
Multi-label learning has attracted significant attention from both acade...
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07/09/2022
Multi-label Classification with High-rank and High-order Label Correlations
Exploiting label correlations is important to multi-label classification...
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06/01/2022
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement
Multi-label learning (MLL) learns from the examples each associated with...
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02/25/2022
Towards Learning Causal Representations from Multi-Instance Bags
Although humans can easily identify the object of interest from groups o...
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10/25/2021
Instance-Dependent Partial Label Learning
Partial label learning (PLL) is a typical weakly supervised learning pro...
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10/22/2021
Prototypical Classifier for Robust Class-Imbalanced Learning
Deep neural networks have been shown to be very powerful methods for man...
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09/19/2009
