Results 11 to 20 of about 8,190,264 (303)
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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Review of Visual Representation Learning [PDF]
Jisuanji kexueRepresentation learning is an important step of artificial intelligence algorithm,where well designed representation can boost downstream tasks.With the development of deep learning in computer vision,visual representation learning has become ...
WANG Shuaiwei, LEI Jie, FENG Zunlei, LIANG Ronghua
doaj +2 more sources
Challenges in representation learning: A report on three machine learning contests
, 2022 S.59-63The ICML 2013 Workshop on Challenges in Representation Learning [http://deeplearning.net/icml2013-workshop-competition] focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal ...
Erhan, Dumitru +27 more
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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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Survey of deep representation learning for speech emotion recognition [PDF]
, 2023 Traditionally, speech emotion recognition (SER) research has relied on manually handcrafted acoustic features using feature engineering. However, the design of handcrafted features for complex SER tasks requires significant manual eort, which impedes ...
Siddique Latif +13 more
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Deep Representation Learning for Speech Emotion Recognition [PDF]
, 2022 The success of machine learning (ML) algorithms generally depends on the quality of data representation or features. Good representations of the data make it easier to develop machine learning predictors or even deep learning (DL) classifiers.
Latif, Siddique
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Deep boundary‑aware clustering by jointly optimizing unsupervised representation learning [PDF]
, 2022 Deep clustering obtains feature representation generally and then performs clustering for high dimension real-world data. However, conventional solutions are two-stage embedding learning-based methods and these two processes are separate and independent,
Li, Lin +9 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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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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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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