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Dynamic Consolidation for Continual Learning
Neural Computation, 2023Abstract Training deep learning models from a stream of nonstationary data is a critical problem to be solved to achieve general artificial intelligence. As a promising solution, the continual learning (CL) technique aims to build intelligent systems that have the plasticity to learn from new information without forgetting the previously
Li, Hang, Ma, Chen, Chen, Xi, Liu, Xue
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Learning continuous potentials from smFRET
Biophysical Journal, 2022ABSTRACTPotential energy landscapes are useful models in describing events such as protein folding and binding. While single molecule fluorescence resonance energy transfer (smFRET) experiments encode information on continuous potentials for the system probed, including rarely visited barriers between putative potential minima, this information is ...
J. Shepard Bryan, Steve Pressé
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Progressive learning: A deep learning framework for continual learning
Neural Networks, 2020Continual learning is the ability of a learning system to solve new tasks by utilizing previously acquired knowledge from learning and performing prior tasks without having significant adverse effects on the acquired prior knowledge. Continual learning is key to advancing machine learning and artificial intelligence.
Haytham M. Fayek +2 more
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Continuous learning about markets
Planning Review, 1992When talking about continuous learning organizations, the word “continuous” bears emphasis. “Continuous” is used in the sense that one does not conduct a single study at a single point in time and then use it as a basis for all following activities. I worked on mapping new product development processes at a major manufacturer of telecommunications gear.
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2016
Kernel learning is the problem of determining the best kernel (either from a dictionary of fixed kernels, or from a smooth space of kernel representations) for a given task. In this paper, we describe a new approach to kernel learning that establishes connections between the Fourier-analytic representation of kernels arising out of Bochner’s theorem ...
John Moeller +4 more
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Kernel learning is the problem of determining the best kernel (either from a dictionary of fixed kernels, or from a smooth space of kernel representations) for a given task. In this paper, we describe a new approach to kernel learning that establishes connections between the Fourier-analytic representation of kernels arising out of Bochner’s theorem ...
John Moeller +4 more
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Childhood Education, 1955
Continuity is the relating of what goes on within the child with what goes on about him. Here is a thought-provoking presentation to help adults understand their role in raising self-selection to conscious deliberative action.
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Continuity is the relating of what goes on within the child with what goes on about him. Here is a thought-provoking presentation to help adults understand their role in raising self-selection to conscious deliberative action.
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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
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