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Alexander Jung
Alex Jung
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2020 – today
- 2024
- [j30]Stefan Hessel, Alexander Jung:
Datenschutzrechtliche Herausforderungen bei der Verwertung von Daten vernetzter Medizinprodukte. Datenschutz und Datensicherheit (dud) 48(5): 289-294 (2024) - [j29]Linli Zhang
, Georgios Karakasidis, Arina Odnoblyudova, Leyla Dogruel, Yu Tian
Explainable empirical risk minimization. Neural Comput. Appl. 36(8): 3983-3996 (2024) - [j28]Jun Yang, Pia Fricker, Alexander Jung
From intangible to tangible: The role of big data and machine learning in walkability studies. Comput. Environ. Urban Syst. 109: 102087 (2024) - [c45]Alexander Jung, Helge Parzyjegla, Peter Danielis:
Opportunistic Protocols for People Counting in Dynamic Networks. CCNC 2024: 198-201 - [c44]Alexander Jung:
Analysis of Total Variation Minimization for Clustered Federated Learning. EUSIPCO 2024: 1027-1031 - [i49]Christophe Nicolet, Antoine Béguin, Matthieu Dreyer, Sébastien Alligné, Alexander Jung, Diogo Cordeiro, Carlos Moreira:
Inertia emulation contribution of Frades 2 variable speed pump-turbine to power network stability. CoRR abs/2404.06299 (2024) - [i48]Alexander Jung, Yasmin Sarcheshmehpour, Amirhossein Mohammadi:
Personalized Federated Learning via Active Sampling. CoRR abs/2409.02064 (2024) - 2023
- [j27]Argyrios Petras
Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology. Comput. Biol. Medicine 156: 106696 (2023) - [j26]Moloud Abdar
Hercules: Deep Hierarchical Attentive Multilevel Fusion Model With Uncertainty Quantification for Medical Image Classification. IEEE Trans. Ind. Informatics 19(1): 274-285 (2023) - [j25]Yasmin Sarcheshmehpour
Clustered Federated Learning via Generalized Total Variation Minimization. IEEE Trans. Signal Process. 71: 4240-4256 (2023) - [c43]Reza Mirzaeifard, Naveen K. D. Venkategowda, Alexander Jung
Moreau Envelope ADMM for Decentralized Weakly Convex Optimization. APSIPA ASC 2023: 1126-1130 - [c42]Alexander Jung
Towards Model-Agnostic Federated Learning over Networks. EUSIPCO 2023: 1614-1618 - [i47]Xu Yang, Yu Tian, Irene Schicker, Alexander Jung:
Wind to start the washing machine? High-Resolution Wind Atlas for Finland. CoRR abs/2303.04403 (2023) - [i46]Yasmin Sarcheshmehpour, Tommi Ryyppo, Victor Mukherjee, Alex Jung:
Design of Induction Machines using Reinforcement Learning. CoRR abs/2306.17626 (2023) - [i45]Reza Mirzaeifard, Naveen K. D. Venkategowda, Alexander Jung, Stefan Werner:
Moreau Envelope ADMM for Decentralized Weakly Convex Optimization. CoRR abs/2308.16752 (2023) - 2022
- [b1]Alexander Jung
Machine Learning - The Basics. Springer 2022, ISBN 978-981-16-8192-9, pp. 1-200 - [j24]Jinping Sui
Dynamic Sparse Subspace Clustering for Evolving High-Dimensional Data Streams. IEEE Trans. Cybern. 52(6): 4173-4186 (2022) - [c41]Hugo Lefeuvre
FlexOS: towards flexible OS isolation. ASPLOS 2022: 467-482 - [i44]Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang
flow-based clustering and spectral clustering: a comparison. CoRR abs/2206.10019 (2022) - 2021
- [j23]Alexander Jung
Local Graph Clustering With Network Lasso. IEEE Signal Process. Lett. 28: 106-110 (2021) - [c40]Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang
Flow-Based Clustering and Spectral Clustering: A Comparison. ACSCC 2021: 1292-1296 - [c39]Alexander Jung
Wayfinder: towards automatically deriving optimal OS configurations. APSys 2021: 115-122 - [c38]Simon Kuenzer, Vlad-Andrei Badoiu
Unikraft: fast, specialized unikernels the easy way. EuroSys 2021: 376-394 - [c37]Yasmin Sarcheshmehpour, M. Leinonen, Alexander Jung
Federated Learning from Big Data Over Networks. ICASSP 2021: 3055-3059 - [i43]Simon Kuenzer, Vlad-Andrei Badoiu, Hugo Lefeuvre, Sharan Santhanam, Alexander Jung, Gaulthier Gain, Cyril Soldani, Costin Lupu, Stefan Teodorescu, Costi Raducanu, Cristian Banu, Laurent Mathy, Razvan Deaconescu, Costin Raiciu, Felipe Huici:
Unikraft: Fast, Specialized Unikernels the Easy Way. CoRR abs/2104.12721 (2021) - [i42]Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang, Alexander Jung:
Networked Federated Multi-Task Learning. CoRR abs/2105.12769 (2021) - [i41]Pasi Pyrrö, Hassan Naseri, Alexander Jung:
Rethinking Drone-Based Search and Rescue with Aerial Person Detection. CoRR abs/2111.09406 (2021) - [i40]Hugo Lefeuvre, Vlad-Andrei Badoiu, Alexander Jung, Stefan Teodorescu, Sebastian Rauch, Felipe Huici, Costin Raiciu, Pierre Olivier:
FlexOS: Towards Flexible OS Isolation. CoRR abs/2112.06566 (2021) - 2020
- [j22]Alexander Jung
Networked Exponential Families for Big Data Over Networks. IEEE Access 8: 202897-202909 (2020) - [j21]Henrik E. C. Cao
Learning Explainable Decision Rules via Maximum Satisfiability. IEEE Access 8: 218180-218185 (2020) - [j20]Alexander Jung
An Information-Theoretic Approach to Personalized Explainable Machine Learning. IEEE Signal Process. Lett. 27: 825-829 (2020) - [j19]Alexander Jung
On the Duality Between Network Flows and Network Lasso. IEEE Signal Process. Lett. 27: 940-944 (2020) - [j18]Nguyen Q. Tran
On the Sample Complexity of Graphical Model Selection From Non-Stationary Samples. IEEE Trans. Signal Process. 68: 17-32 (2020) - [c36]Alexander Jung
Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization. ACSSC 2020: 731-735 - [c35]Sharan Santhanam, Simon Kuenzer, Hugo Lefeuvre
Towards Highly Specialized, POSIX -compliant Software Stacks with Unikraft: Work-in-Progress. EMSOFT 2020: 31-33 - [c34]Timo Huuhtanen, Antti Lankinen, Alexander Jung
Target Tracking on Sensing Surface with Electrical Impedance Tomography. EUSIPCO 2020: 1817-1821 - [c33]Nguyen Q. Tran, Henrik Ambos, Alexander Jung
Classifying Partially Labeled Networked Data VIA Logistic Network Lasso. ICASSP 2020: 3832-3836 - [c32]Timo Huuhtanen, Alexander Jung
Anomaly Location Detection with Electrical Impedance Tomography Using Multilayer Perceptrons. MLSP 2020: 1-6 - [i39]Alexander Jung, Pedro H. J. Nardelli:
An Information-Theoretic Approach to Personalized Explainable Machine Learning. CoRR abs/2003.00484 (2020) - [i38]Alexander Jung:
Local Graph Clustering with Network Lasso. CoRR abs/2004.12199 (2020) - [i37]Alexander Jung:
Explainable Empirical Risk Minimization. CoRR abs/2009.01492 (2020) - [i36]Dick Carrillo, Lam Duc Nguyen
Containing Future Epidemics with Trustworthy Federated Systems for Ubiquitous Warning and Response. CoRR abs/2010.13392 (2020) - [i35]Yasmin Sarcheshmehpour, M. Leinonen, Alexander Jung:
Federated Learning From Big Data Over Networks. CoRR abs/2010.14159 (2020)
2010 – 2019
- 2019
- [j17]Menghao Wu, Yanbin Gao, Alexander Jung
The Actor-Dueling-Critic Method for Reinforcement Learning. Sensors 19(7): 1547 (2019) - [j16]Alexander Jung
Localized Linear Regression in Networked Data. IEEE Signal Process. Lett. 26(7): 1090-1094 (2019) - [j15]Roope Tervo
Short-Term Prediction of Electricity Outages Caused by Convective Storms. IEEE Trans. Geosci. Remote. Sens. 57(11): 8618-8626 (2019) - [j14]Alexander Jung
Semi-Supervised Learning in Network-Structured Data via Total Variation Minimization. IEEE Trans. Signal Process. 67(24): 6256-6269 (2019) - [c31]Alexander Jung, Natalia Vesselinova:
Analysis of Network Lasso for Semi-Supervised Regression. AISTATS 2019: 380-387 - [c30]Timo Huuhtanen, Henrik Ambos, Alexander Jung
Outlier Detection from Non-Smooth Sensor Data. EUSIPCO 2019: 1-5 - [c29]Vladimir Herdt, Daniel Große
Systematic RISC-V based Firmware Design⋆. FDL 2019: 1-8 - [c28]Oleksii Abramenko, Alexander Jung
Graph Signal Sampling via Reinforcement Learning. ICASSP 2019: 3077-3081 - [c27]Jinping Sui, Zhen Liu, Li Liu, Alexander Jung
Sparse Subspace Clustering for Evolving Data Streams. ICASSP 2019: 7455-7459 - [c26]Julen Kahles, Juha Torronen, Timo Huuhtanen, Alexander Jung
Automating Root Cause Analysis via Machine Learning in Agile Software Testing Environments. ICST 2019: 379-390 - [i34]Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi, Ayelet Heimowitz, Yonina C. Eldar:
Semi-supervised Learning in Network-Structured Data via Total Variation Minimization. CoRR abs/1901.09838 (2019) - [i33]Nguyen Q. Tran, Henrik Ambos, Alexander Jung:
Classifying Partially Labeled Networked Data via Logistic Network Lasso. CoRR abs/1903.10926 (2019) - [i32]Alexander Jung, Nguyen Q. Tran:
Localized Linear Regression in Networked Data. CoRR abs/1903.11178 (2019) - [i31]Alexander Jung:
Learning Networked Exponential Families with Network Lasso. CoRR abs/1905.09056 (2019) - [i30]Roope Tervo, Joonas Karjalainen, Alexander Jung:
Short-term prediction of Electricity Outages Caused by Convective Storms. CoRR abs/1907.00662 (2019) - [i29]Alexander Jung:
On the Duality between Network Flows and Network Lasso. CoRR abs/1910.01805 (2019) - [i28]Alexander Jung:
Components of Machine Learning: Binding Bits and FLOPS. CoRR abs/1910.12387 (2019) - [i27]Alexander Jung:
Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization. CoRR abs/1911.00958 (2019) - [i26]Alexander Jung, Ivan Baranov:
Basic Principles of Clustering Methods. CoRR abs/1911.07891 (2019) - 2018
- [j13]Jinping Sui
Dynamic Clustering Scheme for Evolving Data Streams Based on Improved STRAP. IEEE Access 6: 46157-46166 (2018) - [j12]Alexander Jung
The Network Nullspace Property for Compressed Sensing of Big Data Over Networks. Frontiers Appl. Math. Stat. 4: 9 (2018) - [j11]Alexander Jung
On the Complexity of Sparse Label Propagation. Frontiers Appl. Math. Stat. 4: 22 (2018) - [c25]Henrik Ambos, Nguyen Q. Tran, Alexander Jung
Classifying Big Data Over Networks Via The Logistic Network Lasso. ACSSC 2018: 855-858 - [c24]Markku Hinkka, Teemu Lehto, Keijo Heljanko
Classifying Process Instances Using Recurrent Neural Networks. Business Process Management Workshops 2018: 313-324 - [c23]Timo Huuhtanen, Alexander Jung
Predictive Maintenance of Photovoltaic Panels via Deep Learning. DSW 2018: 66-70 - [c22]Roope Tervo, Joonas Karjalainen, Alexander Jung
Predicting Electricity Outages Caused By Convective Storms. DSW 2018: 145-149 - [c21]Madelon Hulsebos, Alexander Jung
The Network Nullspace Property for Compressed Sensing of Big Data Over Networks. ICASSP 2018: 4549-4553 - [c20]Nguyen Q. Tran, Alexander Jung
On the Sample Complexity of Graphical Model Selection from Non-Stationary Samples. ICASSP 2018: 6314-6317 - [c19]Nguyen Q. Tran, Henrik Ambos, Alexander Jung
A Network Compatibility Condition For Compressed Sensing Over Complex Networks. SSP 2018: 50-54 - [c18]Buse Gul Atli, Yoan Miche, Alexander Jung
Network Intrusion Detection Using Flow Statistics. SSP 2018: 70-74 - [i25]Buse Gul Atli, Alexander Jung:
Online Feature Ranking for Intrusion Detection Systems. CoRR abs/1803.00530 (2018) - [i24]Alexander Jung:
On The Complexity of Sparse Label Propagation. CoRR abs/1804.09597 (2018) - [i23]Henrik Ambos, Nguyen Q. Tran, Alexander Jung:
The Logistic Network Lasso. CoRR abs/1805.02483 (2018) - [i22]Alexander Jung:
A Gentle Introduction to Supervised Machine Learning. CoRR abs/1805.05052 (2018) - [i21]Oleksii Abramenko, Alexander Jung:
Graph Signal Sampling via Reinforcement Learning. CoRR abs/1805.05827 (2018) - [i20]Roope Tervo, Joonas Karjalainen, Alexander Jung:
Predicting Electricity Outages Caused by Convective Storms. CoRR abs/1805.07897 (2018) - [i19]Alexander Jung:
Analysis of Network Lasso For Semi-Supervised Regression. CoRR abs/1808.07249 (2018) - [i18]Markku Hinkka, Teemu Lehto, Keijo Heljanko
Classifying Process Instances Using Recurrent Neural Networks. CoRR abs/1809.05896 (2018) - 2017
- [j10]Alexander Jung
A Fixed-Point of View on Gradient Methods for Big Data. Frontiers Appl. Math. Stat. 3: 18 (2017) - [j9]Alexander Jung
When Is Network Lasso Accurate? Frontiers Appl. Math. Stat. 3: 28 (2017) - [c17]Alexandru Mara, Alexander Jung
Recovery conditions and sampling strategies for network Lasso. ACSSC 2017: 405-409 - [c16]Luiza Sayfullina, Eric Malmi, Yiping Liao, Alexander Jung
Domain Adaptation for Resume Classification Using Convolutional Neural Networks. AIST 2017: 82-93 - [c15]Markku Hinkka, Teemu Lehto, Keijo Heljanko
Structural Feature Selection for Event Logs. Business Process Management Workshops 2017: 20-35 - [c14]Florian Roemer, Marcus Grossmann, Tobias Schoen, Roland Gruber, Alexander Jung, Steven Oeckl, Giovanni Del Galdo:
Differential SART for sub-Nyquist tomographic reconstruction in presence of misalignments. EUSIPCO 2017: 2354-2358 - [c13]Gita Babazadeh Eslamlou, Alexander Jung
Smooth graph signal recovery via efficient Laplacian solvers. ICASSP 2017: 5915-5919 - [c12]Nguyen Tran Quang, Alexander Jung
Learning conditional independence structure for high-dimensional uncorrelated vector processes. ICASSP 2017: 5920-5924 - [i17]Nguyen Tran Quang, Alexander Jung:
On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes. CoRR abs/1701.04724 (2017) - [i16]Saeed Basirian, Alexander Jung:
Random Walk Sampling for Big Data over Networks. CoRR abs/1704.04799 (2017) - [i15]Alexander Jung:
The Network Nullspace Property for Compressed Sensing of Big Data over Networks. CoRR abs/1705.04379 (2017) - [i14]Luiza Sayfullina, Eric Malmi, Yiping Liao, Alex Jung:
Domain Adaptation for Resume Classification Using Convolutional Neural Networks. CoRR abs/1707.05576 (2017) - [i13]Alexandru Mara, Alexander Jung:
Recovery Conditions and Sampling Strategies for Network Lasso. CoRR abs/1709.01402 (2017) - [i12]Markku Hinkka, Teemu Lehto, Keijo Heljanko, Alexander Jung:
Structural Feature Selection for Event Logs. CoRR abs/1710.02823 (2017) - [i11]Nguyen Q. Tran, Saeed Basirian, Alexander Jung:
When is Network Lasso Accurate: The Vector Case. CoRR abs/1710.03942 (2017) - 2016
- [j8]Alexander Jung
On the Minimax Risk of Dictionary Learning. IEEE Trans. Inf. Theory 62(3): 1501-1515 (2016) - [c11]Gabor Hannak, Peter Berger, Gerald Matz
Efficient graph signal recovery over big networks. ACSSC 2016: 1839-1843 - [c10]Gita Babazadeh Eslamlou, Alexander Jung
Graph signal recovery from incomplete and noisy information using approximate message passing. ICASSP 2016: 6170-6174 - [c9]Alexander Jung
Scalable graph signal recovery for big data over networks. SPAWC 2016: 1-6 - [i10]Nguyen Tran Quang, Alexander Jung:
Learning conditional independence structure for high-dimensional uncorrelated vector processes. CoRR abs/1609.03772 (2016) - [i9]Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Alexander Jung:
Big Data Frameworks: A Comparative Study. CoRR abs/1610.09962 (2016) - [i8]Alexander Jung, Alfred O. Hero III, Alexandru Mara, Sabeur Aridhi:
Scalable Semi-Supervised Learning over Networks using Nonsmooth Convex Optimization. CoRR abs/1611.00714 (2016) - [i7]Alexander Jung:
Sparse Label Propagation. CoRR abs/1612.01414 (2016) - 2015
- [j7]Alexander Jung
Graphical LASSO based Model Selection for Time Series. IEEE Signal Process. Lett. 22(10): 1781-1785 (2015) - [j6]Alexander Jung
Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach. IEEE Trans. Signal Process. 63(21): 5677-5690 (2015) - [c8]Gabor Hannak, Martin Mayer, Alexander Jung
Joint channel estimation and activity detection for multiuser communication systems. ICC Workshops 2015: 2086-2091 - [i6]Alexander Jung, Yonina C. Eldar, Norbert Görtz:
On the Minimax Risk of Dictionary Learning. CoRR abs/1507.05498 (2015) - 2014
- [j5]Norbert Goertz, Chunli Guo, Alexander Jung
Iterative Recovery of Dense Signals from Incomplete Measurements. IEEE Signal Process. Lett. 21(9): 1059-1063 (2014) - [j4]Alexander Jung
The RKHS Approach to Minimum Variance Estimation Revisited: Variance Bounds, Sufficient Statistics, and Exponential Families. IEEE Trans. Inf. Theory 60(7): 4050-4065 (2014) - [j3]Alexander Jung
Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An RKHS Approach. IEEE Trans. Inf. Theory 60(10): 6555-6575 (2014) - [c7]Gabor Hannak, Alexander Jung, Norbert Goertz:
On the information-theoretic limits of graphical model selection for Gaussian time series. EUSIPCO 2014: 516-520 - [c6]Alexander Jung, Yonina C. Eldar, Norbert Goertz:
Performance limits of dictionary learning for sparse coding. EUSIPCO 2014: 765-769 - [c5]Alexander Jung
Compressive nonparametric graphical model selection for time series. ICASSP 2014: 769-773 - 2013
- [j2]Alexander Jung
Compressive Spectral Estimation for Nonstationary Random Processes. IEEE Trans. Inf. Theory 59(5): 3117-3138 (2013) - [i5]Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch, Zvika Ben-Haim, Yonina C. Eldar:
Minimum Variance Estimation of a Sparse Vector within the Linear Gaussian Model: An RKHS Approach. CoRR abs/1304.3886 (2013) - 2011
- [j1]Alexander Jung
Unbiased Estimation of a Sparse Vector in White Gaussian Noise. IEEE Trans. Inf. Theory 57(12): 7856-7876 (2011) - [c4]Alexander Jung
Performance bounds for sparse parametric covariance estimation in Gaussian models. ICASSP 2011: 4156-4159 - [c3]Sebastian Schmutzhard
Minimum variance estimation for the sparse signal in noise model. ISIT 2011: 124-128 - [i4]Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch, Alfred O. Hero III:
Performance Bounds for Sparse Parametric Covariance Estimation in Gaussian Models. CoRR abs/1101.3838 (2011) - 2010
- [c2]Alexander Jung
On unbiased estimation of sparse vectors corrupted by Gaussian noise. ICASSP 2010: 3990-3993 - [i3]Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Yonina C. Eldar:
On Unbiased Estimation of Sparse Vectors Corrupted by Gaussian Noise. CoRR abs/1002.0110 (2010) - [i2]Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Yonina C. Eldar:
Unbiased Estimation of a Sparse Vector in White Gaussian Noise. CoRR abs/1005.5697 (2010) - [i1]Sebastian Schmutzhard, Alexander Jung, Franz Hlawatsch, Zvika Ben-Haim, Yonina C. Eldar:
A Lower Bound on the Estimator Variance for the Sparse Linear Model. CoRR abs/1009.3353 (2010)
2000 – 2009
- 2009
- [c1]Alexander Jung
Compressive spectral estimation for nonstationary random processes. ICASSP 2009: 3029-3032
Coauthor Index
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