RESEARCH.FI

Advances in Weakly Supervised Learning of Morphology

Avoin saatavuus

Kohonen, Oskar

Aalto University

2015

Developing a supervised machine learning model for predicting perioperative acute kidney injury in arthroplasty patients

Vertaisarvioitu

Avoin saatavuus

DOI

10.1016/j.compbiomed.2022.105351

Nikkinen, Okke; Kolehmainen, Timo; Aaltonen, Toni; Jämsä, Elias; Alahuhta, Seppo; Vakkala, Merja

Computers in biology and medicine

2022

Minimal learning machine : a novel supervised distance-based approach for regression and classification

Vertaisarvioitu

DOI

10.1016/j.neucom.2014.11.073

Amauri Holanda de Souza JuÌnior; Francesco Corona; Guilherme A. Barreto; Yoan Miche; Amaury Lendass...

Neurocomputing

2015

Extreme learning machine based supervised subspace learning

Vertaisarvioitu

DOI

10.1016/j.neucom.2015.04.083

Iosifidis, Alexandros

Neurocomputing

2015

Development of a late-life dementia prediction index with supervised machine learning in the population-based CAIDE study

Vertaisarvioitu

Avoin saatavuus

Pekkala, Timo; Hall, Anette; Lötjönen, Jyrki; Mattila, Jussi; Soininen, Hilkka; Ngandu, Tiia; Laatik...

Journal of Alzheimer's disease

2017

A kernel-learning approach to semi-supervised clustering with relative distance comparisons

Vertaisarvioitu

Amid, Ehsan; Gionis, Aristides; Ukkonen, Antti

SPRINGER

2015

Self-supervised representation learning from electroencephalography signals

Vertaisarvioitu

DOI

10.1109/MLSP.2019.8918693

Banville, Hubert; Albuquerque, Isabela; Hyvärinen, Aapo; Moffat, Grame; Engemann, Denis-Alexander; G...

IEEE International Workshop on Machine Learning for Signal Processing

2019

Semi-Supervised Few-Shot Class-Incremental Learning

Vertaisarvioitu

Avoin saatavuus

DOI

10.1109/icip42928.2021.9506346

Cui, Yawen; Xiong, Wuti; Tavakolian, Mohammad; Liu, Li

Proceedings : International Conference on Image Processing

2021

Uncovering the structure of clinical EEG signals with self-supervised learning

Vertaisarvioitu

DOI

10.1088/1741-2552/abca18

Banville, Hubert; Chehab, Omar; Hyvarinen, Aapo; Engemann, Denis-Alexander; Gramfort, Alexandre

Journal of Neural Engineering

2021

Enhancing Predictive Models for Assessing 5G Exposure Effects on Human Health and Cognition through Supervised Machine Learning: A Multi-Stage Feature Selection Approach

Vertaisarvioitu

DOI

10.15199/48.2024.06.23

Sofri, Tasneem; Andrew, Allan Melvin; Rahim, Hasliza A.; Nishizaki, Hiromitsu; Kamarudin, Latifah Mu...

Przeglad elektrotechniczny

2024

Advances in Weakly Supervised Learning of Morphology

Avoin saatavuus

2015

Developing a supervised machine learning model for predicting perioperative acute kidney injury in arthroplasty patients

Vertaisarvioitu

Avoin saatavuus

DOI

10.1016/j.compbiomed.2022.105351

2022

Minimal learning machine : a novel supervised distance-based approach for regression and classification

Vertaisarvioitu

DOI

10.1016/j.neucom.2014.11.073

2015

Extreme learning machine based supervised subspace learning

Vertaisarvioitu

DOI

10.1016/j.neucom.2015.04.083

2015

Development of a late-life dementia prediction index with supervised machine learning in the population-based CAIDE study

Vertaisarvioitu

Avoin saatavuus

2017

A kernel-learning approach to semi-supervised clustering with relative distance comparisons

Vertaisarvioitu

2015

Self-supervised representation learning from electroencephalography signals

Vertaisarvioitu

DOI

10.1109/MLSP.2019.8918693

2019

Semi-Supervised Few-Shot Class-Incremental Learning

Vertaisarvioitu

Avoin saatavuus

DOI

10.1109/icip42928.2021.9506346

2021

Uncovering the structure of clinical EEG signals with self-supervised learning

Vertaisarvioitu

DOI

10.1088/1741-2552/abca18

2021

Enhancing Predictive Models for Assessing 5G Exposure Effects on Human Health and Cognition through Supervised Machine Learning: A Multi-Stage Feature Selection Approach

Vertaisarvioitu

DOI

10.15199/48.2024.06.23

2024

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Advances in Weakly Supervised Learning of Morphology

Developing a supervised machine learning model for predicting perioperative acute kidney injury in arthroplasty patients

Minimal learning machine : a novel supervised distance-based approach for regression and classification

Extreme learning machine based supervised subspace learning

Development of a late-life dementia prediction index with supervised machine learning in the population-based CAIDE study

A kernel-learning approach to semi-supervised clustering with relative distance comparisons

Self-supervised representation learning from electroencephalography signals

Semi-Supervised Few-Shot Class-Incremental Learning

Uncovering the structure of clinical EEG signals with self-supervised learning

Enhancing Predictive Models for Assessing 5G Exposure Effects on Human Health and Cognition through Supervised Machine Learning: A Multi-Stage Feature Selection Approach

Advances in Weakly Supervised Learning of Morphology

Developing a supervised machine learning model for predicting perioperative acute kidney injury in arthroplasty patients

Minimal learning machine : a novel supervised distance-based approach for regression and classification

Extreme learning machine based supervised subspace learning

Development of a late-life dementia prediction index with supervised machine learning in the population-based CAIDE study

A kernel-learning approach to semi-supervised clustering with relative distance comparisons

Self-supervised representation learning from electroencephalography signals

Semi-Supervised Few-Shot Class-Incremental Learning

Uncovering the structure of clinical EEG signals with self-supervised learning

Enhancing Predictive Models for Assessing 5G Exposure Effects on Human Health and Cognition through Supervised Machine Learning: A Multi-Stage Feature Selection Approach