Results 11 to 20 of about 7,883,935 (303)

Graph Representation Learning [PDF]

ESANN 2023 proceesdings, 2023
In a broad range of real-world machine learning applications, representing examples as graphs is crucial to avoid a loss of information. For this reason, in the last few years, the definition of machine learning methods, particularly neural networks, for graph-structured inputs has been gaining increasing attention.
Davide Bacciu, Federico Errica, Alessio Micheli, Nicolò Navarin, Luca Pasa, Marco Podda, Daniele Zambon   +6 more
openaire   +5 more sources

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
core   +1 more source

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, Carrier, Pierre Luc, Athanasakis, Dimitris, Goodfellow, Ian J., Lee, Dong-Hyun, Zhou, Yingbo, Tang, Yichuan, Hamner, Ben, Li, Ruifan, Wang, Xiaojie, Milakov, Maxim, Cukierski, Will, Xie, Jingjing, Thaler, David, Courville, Aaron, Bergstra, James, Xu, Bing, Chuang, Zhang, Feng, Fangxiang, Ramaiah, Chetan, Ionescu, Radu, Romaszko, Lukasz, Shawe-Taylor, John, Park, John, Popescu, Marius, Grozea, Cristian, Mirza, Mehdi, Bengio, Yoshua   +27 more
core   +3 more sources

Dual Space Latent Representation Learning for Image Representation

Mathematics, 2023
Semi-supervised non-negative matrix factorization (NMF) has achieved successful results due to the significant ability of image recognition by a small quantity of labeled information.
Yulei Huang, Ziping Ma, Huirong Li, Jingyu Wang   +3 more
doaj   +1 more source

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, Latif, Siddique, Sara Khalifa, Rajib Rana, Raja Jurdak, Junaid Qadir, Rana, Rajib, Qadir, Junaid, Schuller, Bjorn, Schuller, Björn W., Khalifa, Sara, Jurdak, Raja, Björn Schuller   +12 more
core   +1 more source

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, Gregory M. Provan, Padhraic Smyth   +2 more
openaire   +2 more sources

Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture

Scientific Reports, 2023
The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, we present a principled veridical data science methodology for quantitative histology that shifts focus from image-level investigations towards neuron ...
Andrija Štajduhar, Tomislav Lipić, Sven Lončarić, Miloš Judaš, Goran Sedmak   +4 more
doaj   +1 more source

Mathematical Representation Ability of Students on Linear Program Material in Terms of Learning Interests in Problem Based Learning

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
doaj   +1 more source

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, Nicolas Perrin-Gilbert, Alex Coninx, Stéphane Doncieux   +3 more
doaj   +1 more source

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, Emiliano Panieri, Višnja Stepanić, Hande Gurer-Orhan, Luciano Saso   +4 more
doaj   +1 more source