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Reduce the Difficulty of Incremental Learning With Self-Supervised Learning
Incremental learning requires a learning model to learn new tasks without forgetting the learned tasks continuously. However, when a deep learning model learns new tasks, it will catastrophically forget tasks it has learned before.
Linting Guan, Yan Wu
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Incremental Cost-Sensitive Support Vector Machine With Linear-Exponential Loss
Incremental learning or online learning as a branch of machine learning has attracted more attention recently. For large-scale problems and dynamic data problem, incremental learning overwhelms batch learning, because of its efficient treatment for new ...
Yue Ma, Kun Zhao, Qi Wang, Yingjie Tian
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Deep Error-Correcting Output Codes
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval.
Li-Na Wang +4 more
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An incremental approach to genetic algorithms based classification [PDF]
Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental
Guan, SU, Zhu, F
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Class decomposition for GA-based classifier agents – A Pitt approach [PDF]
Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental
Guan, SU, Zhu, F
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Hierarchical incremental class learning with reduced pattern training [PDF]
Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but closer examination reveals areas for potential improvement.
Bao, C, Guan, SU, Sun, RT
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An Optimized Class Incremental Learning Network with Dynamic Backbone Based on Sonar Images
Class incremental learning with sonar images introduces a new dimension to underwater target recognition. Directly applying networks designed for optical images to our constructed sonar image dataset (SonarImage20) results in significant catastrophic ...
Xinzhe Chen, Hong Liang
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Classification-oriented Incremental Dictionary Learning Algorithm [PDF]
Aiming at the problem that the computation cost of the traditional classification-oriented dictionary learning algorithms is too expensive on big datasets,this paper proposes a novel classification-oriented incremental dictionary learning algorithm.In ...
ZHANG Zhiwu,JING Xiaoyuan,WU Fei
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Class Incremental Learning Method Integrating Balance Weight and Self-supervision [PDF]
In view of the catastrophic forgetting phenomenon of knowledge in class incremental learning in image classification, the existing class incremental learning methods focus on the correction of the unbalanced offset of the model classification layer ...
GONG Jiayi, XU Xinlei, XIAO Ting, WANG Zhe
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Using Domain Adaptation for Incremental SVM Classification of Drift Data
A common assumption in machine learning is that training data is complete, and the data distribution is fixed. However, in many practical applications, this assumption does not hold.
Junya Tang, Kuo-Yi Lin, Li Li
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