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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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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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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Self-incremental learning vector quantization with human cognitive biases. [PDF]
Sci Rep, 2021 Manome N +4 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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Analysis of Chinese Patents associated with Incremental Clustering Algorithms: A Review
Journal of Computing Research and Innovation, 2022 With the advent of Internet-of-Things (IoT) and overall Information-Technology world, an enormous amount of data is getting generated dynamically and in real-time mode, in almost all domains of research and application systems.
Archana Chaudhari +2 more
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Class-Incremental Learning of Convolutional Neural Networks Based on Double Consolidation Mechanism
IEEE Access, 2020 Class-incremental learning is a model learning technique that can help classification models incrementally learn about new target classes and realize knowledge accumulation.
Leilei Jin, Hong Liang, Changsheng Yang
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Reduce the Difficulty of Incremental Learning With Self-Supervised Learning
IEEE Access, 2021 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
IEEE Access, 2020 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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