Results 11 to 20 of about 375,534 (168)
Learning Overcomplete Representations [PDF]
Neural Computation, 2000 In an overcomplete basis, the number of basis vectors is greater than the dimensionality of the input, and the representation of an input is not a unique combination of basis vectors. Overcomplete representations have been advocated because they have greater robustness in the presence of noise, can be sparser, and can have greater flexibility in ...
Michael S. Lewicki +1 more
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Representation Learning by Learning to Count [PDF]
2017 IEEE International Conference on Computer Vision (ICCV), 2017 ICCV 2017(oral)
Mehdi Noroozi +2 more
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Learning with Probabilistic Representations [PDF]
Machine Learning, 1997 1. Introduction and motivationMachine learning cannot occur without some means to represent the learned knowledge.Researchers have long recognized the influence of representational choices, and the majorparadigms in machine learning are organized not around induction algorithms or perfor-manceelementsasmuchasaroundrepresentationalclasses ...
Pat Langley +2 more
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Journal of Medives: Journal of Mathematics Education IKIP Veteran Semarang, 2023 This study aims to determine the completeness of the implementation of Problem-Based Learning (PBL) to the achievement of students' mathematical representation skills, determine the influence of learning interest on the mathematical representation ...
Safa Agrita Hilsania, Masrukan Masrukan
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Exploratory State Representation Learning
Frontiers in Robotics and AI, 2022 Not having access to compact and meaningful representations is known to significantly increase the complexity of reinforcement learning (RL). For this reason, it can be useful to perform state representation learning (SRL) before tackling RL tasks ...
Astrid Merckling +3 more
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IEEE Access, 2021 Machine learning has been widely applied in the fields of biomedicine, computational biology, bioinformatics, image processing, and so on. The performance of machine learning methods mainly relies on feature representation that is the mapping from ...
Feifei Cui +5 more
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Involvement of NRF2 in Breast Cancer and Possible Therapeutical Role of Polyphenols and Melatonin
Molecules, 2021 Oxidative stress is defined as a disturbance in the prooxidant/antioxidant balance in favor of the former and a loss of control over redox signaling processes, leading to potential biomolecular damage.
Alev Tascioglu Aliyev +4 more
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Journal of Medives: Journal of Mathematics Education IKIP Veteran Semarang, 2022 This research is a descriptive study that aims to explain students' mathematical representation abilities in solving AKM numeracy questions after problem based learning is implemented, to explain the implementation of the problem based learning learning ...
Karenina Rizka Alifa +3 more
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A Manifold Learning Perspective on Representation Learning: Learning Decoder and Representations without an Encoder [PDF]
Entropy, 2021 Autoencoders are commonly used in representation learning. They consist of an encoder and a decoder, which provide a straightforward method to map n-dimensional data in input space to a lower m-dimensional representation space and back. The decoder itself defines an m-dimensional manifold in input space.
Viktoria Schuster, Anders Krogh
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Learning internal representations [PDF]
Proceedings of the eighth annual conference on Computational learning theory - COLT '95, 1995 Probably the most important problem in machine learning is the preliminary biasing of a learner's hypothesis space so that it is small enough to ensure good generalisation from reasonable training sets, yet large enough that it contains a good solution to the problem being learnt.
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