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Alexander Jung (mlbook.cs.aalto.fi)
Alexander Jung (mlbook.cs.aalto.fi)
Associate Professor, Aalto University
Bestätigte E-Mail-Adresse bei aalto.fi - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Machine Learning: The Basics
A Jung
https://link.springer.com/book/10.1007/978-981-16-8193-6, 2022
101*2022
Predictive maintenance of photovoltaic panels via deep learning
T Huuhtanen, A Jung
2018 ieee data science workshop (dsw), 66-70, 2018
672018
Graphical lasso based model selection for time series
A Jung, G Hannak, N Goertz
IEEE Signal Processing Letters 22 (10), 1781-1785, 2015
672015
Joint channel estimation and activity detection for multiuser communication systems
G Hannak, M Mayer, A Jung, G Matz, N Goertz
2015 IEEE International Conference on Communication Workshop (ICCW), 2086-2091, 2015
642015
Semi-supervised learning in network-structured data via total variation minimization
A Jung, AO Hero III, AC Mara, S Jahromi, A Heimowitz, YC Eldar
IEEE Transactions on Signal Processing 67 (24), 6256-6269, 2019
392019
When is network lasso accurate?
A Jung, N Tran, A Mara
Frontiers in Applied Mathematics and Statistics 3, 28, 2018
392018
On the minimax risk of dictionary learning
A Jung, YC Eldar, N Görtz
IEEE Transactions on Information Theory 62 (3), 1501-1515, 2016
382016
Classifying process instances using recurrent neural networks
M Hinkka, T Lehto, K Heljanko, A Jung
Business Process Management Workshops: BPM 2018 International Workshops …, 2019
372019
Localized linear regression in networked data
A Jung, N Tran
IEEE Signal Processing Letters 26 (7), 1090-1094, 2019
332019
Learning the conditional independence structure of stationary time series: A multitask learning approach
A Jung
IEEE Transactions on Signal Processing 63 (21), 5677-5690, 2015
332015
Hercules: Deep Hierarchical Attentive Multilevel Fusion Model With Uncertainty Quantification for Medical Image Classification
M Abdar, MA Fahami, L Rundo, P Radeva, AF Frangi, UR Acharya, ...
IEEE Transactions on Industrial Informatics 19 (1), 274-285, 2022
292022
Automating root cause analysis via machine learning in agile software testing environments
J Kahles, J Törrönen, T Huuhtanen, A Jung
2019 12th IEEE Conference on Software Testing, Validation and Verification …, 2019
282019
A fixed-point of view on gradient methods for big data
A Jung
Frontiers in Applied Mathematics and Statistics 3, 18, 2017
282017
Semi-supervised learning via sparse label propagation
A Jung, AO Hero III, A Mara, S Jahromi
arXiv preprint arXiv:1612.01414, 2016
262016
Machine learning: Basic principles
A Jung
arXiv preprint arXiv:1805.05052, 2018
242018
Unbiased estimation of a sparse vector in white Gaussian noise
A Jung, Z Ben-Haim, F Hlawatsch, YC Eldar
IEEE transactions on information theory 57 (12), 7856-7876, 2011
242011
Predicting power outages caused by extratropical storms
R Tervo, I Láng, A Jung, A Mäkelä
Natural Hazards and Earth System Sciences Discussions 2020, 1-26, 2020
232020
An information-theoretic approach to personalized explainable machine learning
A Jung, PHJ Nardelli
IEEE Signal Processing Letters 27, 825-829, 2020
232020
Domain adaptation for resume classification using convolutional neural networks
L Sayfullina, E Malmi, Y Liao, A Jung
Analysis of Images, Social Networks and Texts: 6th International Conference …, 2018
232018
Compressive spectral estimation for nonstationary random processes
A Jung, G Tauböck, F Hlawatsch
IEEE Transactions on Information Theory 59 (5), 3117-3138, 2013
232013
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