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DILS: depth incremental learning strategy [PDF]
Frontiers in Neurorobotics, 2023 There exist various methods for transferring knowledge between neural networks, such as parameter transfer, feature sharing, and knowledge distillation.
Yanmei Wang +14 more
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Three types of incremental learning. [PDF]
Nat Mach Intell, 2022 AbstractIncrementally learning new information from a non-stationary stream of data, referred to as ‘continual learning’, is a key feature of natural intelligence, but a challenging problem for deep neural networks. In recent years, numerous deep learning methods for continual learning have been proposed, but comparing their performances is difficult ...
van de Ven GM, Tuytelaars T, Tolias AS.
europepmc +4 more sources
Incremental Learning of Latent Forests [PDF]
IEEE Access, 2020 In the analysis of real-world data, it is useful to learn a latent variable model that represents the data generation process. In this setting, latent tree models are useful because they are able to capture complex relationships while being easily ...
Fernando Rodriguez-Sanchez +2 more
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Uncertainty alters the balance between incremental learning and episodic memory [PDF]
eLife, 2022 A key question in decision-making is how humans arbitrate between competing learning and memory systems to maximize reward. We address this question by probing the balance between the effects, on choice, of incremental trial-and-error learning versus ...
Jonathan Nicholas +2 more
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DeeSIL: Deep-Shallow Incremental Learning [PDF]
, 2018 Incremental Learning (IL) is an interesting AI problem when the algorithm is assumed to work on a budget. This is especially true when IL is modeled using a deep learning approach, where two com- plex challenges arise due to limited memory, which induces
AL Ginsca +4 more
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End-to-end Incremental Learning [PDF]
, 2018 Although deep learning approaches have stood out in recent years due to their state-of-the-art results, they continue to suffer from (catastrophic forgetting), a dramatic decrease in overall performance when training with new classes added incrementally.
Alahari, Karteek +4 more
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Learning Entropy: Multiscale Measure for Incremental Learning [PDF]
Entropy, 2013 First, this paper recalls a recently introduced method of adaptive monitoring of dynamical systems and presents the most recent extension with a multiscale-enhanced approach.
Ivo Bukovsky
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An Appraisal of Incremental Learning Methods [PDF]
Entropy, 2020 As a special case of machine learning, incremental learning can acquire useful knowledge from incoming data continuously while it does not need to access the original data.
Yong Luo +3 more
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Development and research of a neural network alternate incremental learning algorithm
Компьютерная оптика, 2023 In this paper, the relevance of developing methods and algorithms for neural network incremental learning is shown. Families of incremental learning techniques are presented. A possibility of using the extreme learning machine for incremental learning is
A.A. Orlov, E.S. Abramova
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DILRS: Domain-Incremental Learning for Semantic Segmentation in Multi-Source Remote Sensing Data
Remote Sensing, 2023 With the exponential growth in the speed and volume of remote sensing data, deep learning models are expected to adapt and continually learn over time.
Xue Rui +4 more
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