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Incremental Learning From Stream Data
IEEE Transactions on Neural Networks, 2011Recent years have witnessed an incredibly increasing interest in the topic of incremental learning. Unlike conventional machine learning situations, data flow targeted by incremental learning becomes available continuously over time. Accordingly, it is desirable to be able to abandon the traditional assumption of the availability of representative ...
He, Haibo +3 more
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Identity Recognition by Incremental Learning
2018Face recognition systems nowadays benefit from the improved performance of new classification models combined with the availability of large datasets of face images and the increase of computational power.
del Bimbo A. +3 more
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Incremental Machine Learning: Incremental Classification
2022 7th International Conference on Computer Science and Engineering (UBMK), 2022Engin Baysal, Cüneyt Bayılmış
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1990
Chapters 3 through 5 have described how incremental version-space merging can be used to learn incrementally from a sequence of training instances. More generally, however, the information processed by incremental version-space merging need not correspond directly training data; as long as a piece of information can be converted into a version space of
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Chapters 3 through 5 have described how incremental version-space merging can be used to learn incrementally from a sequence of training instances. More generally, however, the information processed by incremental version-space merging need not correspond directly training data; as long as a piece of information can be converted into a version space of
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2006
Learning with adaptivity is a key issue in many nowadays applications. The most important aspect of such an issue is incremental learning (IL). This latter seeks to equip learning algorithms with the ability to deal with data arriving over long periods of time. Once used during the learning process, old data is never used in subsequent learning stages.
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Learning with adaptivity is a key issue in many nowadays applications. The most important aspect of such an issue is incremental learning (IL). This latter seeks to equip learning algorithms with the ability to deal with data arriving over long periods of time. Once used during the learning process, old data is never used in subsequent learning stages.
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Neocognitron capable of incremental learning
Neural Networks, 2003This paper proposes a new neocognitron that accepts incremental learning, without giving a severe damage to old memories or reducing learning speed. The new neocognitron uses a competitive learning, and the learning of all stages of the hierarchical network progresses simultaneously.
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Incremental learning of logic programs
1995In this paper, we identify a class of polynomial-time learnable logic programs. These programs can be learned from examples in an incremental fashion using the already defined predicates as background knowledge. Our class properly contains the class of innermost simple programs of [20] and the class of hereditary programs of [12,13].
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
exaly
Incremental Learning, Incremental Backdoor Threats
IEEE Transactions on Dependable and Secure ComputingWenbo Jiang +4 more
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