On unbiased estimation of sparse vectors corrupted by Gaussian noise. - Alexander Jung; Zvika Ben-Haim; Franz Hlawatsch; Yonina C. Eldar (ICASSP, 2010)

A Lower Bound on the Estimator Variance for the Sparse Linear Model - Sebastian Schmutzhard; Alexander Jung; Franz Hlawatsch; Zvika Ben-Haim; Yonina C. Eldar (CoRR, 2010)

Performance bounds for sparse parametric covariance estimation in Gaussian models. - Alexander Jung; Sebastian Schmutzhard; Franz Hlawatsch; Alfred O. Hero III (ICASSP, 2011)

Minimum variance estimation for the sparse signal in noise model. - Sebastian Schmutzhard; Alexander Jung; Franz Hlawatsch (ISIT, 2011)

Unbiased Estimation of a Sparse Vector in White Gaussian Noise. - Alexander Jung; Zvika Ben-Haim; Franz Hlawatsch; Yonina C. Eldar (IEEE Trans. Inf. Theory, 2011)

Compressive Spectral Estimation for Nonstationary Random Processes. - Alexander Jung; Georg Tauböck; Franz Hlawatsch (IEEE Trans. Inf. Theory, 2013)

On the information-theoretic limits of graphical model selection for Gaussian time series. - Gabor Hannak; Alexander Jung; Norbert Goertz (EUSIPCO, 2014)

Performance limits of dictionary learning for sparse coding. - Alexander Jung; Yonina C. Eldar; Norbert Goertz (EUSIPCO, 2014)

Compressive nonparametric graphical model selection for time series. - Alexander Jung; Reinhard Heckel; Helmut Bölcskei; Franz Hlawatsch (ICASSP, 2014)

Iterative Recovery of Dense Signals from Incomplete Measurements. - Norbert Goertz; Chunli Guo; Alexander Jung; Mike E. Davies 001; Gerhard Doblinger (IEEE Signal Process. Lett., 2014)

The RKHS Approach to Minimum Variance Estimation Revisited: Variance Bounds, Sufficient Statistics, and Exponential Families. - Alexander Jung; Sebastian Schmutzhard; Franz Hlawatsch (IEEE Trans. Inf. Theory, 2014)

Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An RKHS Approach. - Alexander Jung; Sebastian Schmutzhard; Franz Hlawatsch; Zvika Ben-Haim; Yonina C. Eldar (IEEE Trans. Inf. Theory, 2014)

Joint channel estimation and activity detection for multiuser communication systems. - Gabor Hannak; Martin Mayer; Alexander Jung; Gerald Matz; Norbert Goertz (ICC Workshops, 2015)

Graphical LASSO based Model Selection for Time Series. - Alexander Jung; Gabor Hannak; Norbert Goertz (IEEE Signal Process. Lett., 2015)

Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach. - Alexander Jung (IEEE Trans. Signal Process., 2015)

Efficient graph signal recovery over big networks. - Gabor Hannak; Peter Berger; Gerald Matz; Alexander Jung (ACSSC, 2016)

Graph signal recovery from incomplete and noisy information using approximate message passing. - Gita Babazadeh Eslamlou; Alexander Jung; Norbert Goertz; Mehdi Fereydooni (ICASSP, 2016)

Scalable graph signal recovery for big data over networks. - Alexander Jung; Peter Berger; Gabor Hannak; Gerald Matz (SPAWC, 2016)

Big Data Frameworks: A Comparative Study. - Wissem Inoubli; Sabeur Aridhi; Haithem Mezni; Alexander Jung (CoRR, 2016)

Sparse Label Propagation. - Alexander Jung (CoRR, 2016)

Scalable Semi-Supervised Learning over Networks using Nonsmooth Convex Optimization. - Alexander Jung; Alfred O. Hero III; Alexandru Mara; Sabeur Aridhi (CoRR, 2016)

On the Minimax Risk of Dictionary Learning. - Alexander Jung; Yonina C. Eldar; Norbert Goertz (IEEE Trans. Inf. Theory, 2016)

Recovery conditions and sampling strategies for network Lasso. - Alexandru Mara; Alexander Jung (ACSSC, 2017)

Domain Adaptation for Resume Classification Using Convolutional Neural Networks. - Luiza Sayfullina; Eric Malmi; Yiping Liao; Alexander Jung (AIST, 2017)

Structural Feature Selection for Event Logs. - Markku Hinkka; Teemu Lehto; Keijo Heljanko; Alexander Jung (Business Process Management Workshops, 2017)

Differential SART for sub-Nyquist tomographic reconstruction in presence of misalignments. - Florian Roemer; Marcus Grossmann; Tobias Schoen; Roland Gruber; Alexander Jung; Steven Oeckl; Giovanni Del Galdo (EUSIPCO, 2017)

Smooth graph signal recovery via efficient Laplacian solvers. - Gita Babazadeh Eslamlou; Alexander Jung; Norbert Goertz (ICASSP, 2017)

Learning conditional independence structure for high-dimensional uncorrelated vector processes. - Nguyen Tran Quang; Alexander Jung (ICASSP, 2017)

Random Walk Sampling for Big Data over Networks. - Saeed Basirian; Alexander Jung (CoRR, 2017)

The Network Nullspace Property for Compressed Sensing of Big Data over Networks. - Alexander Jung (CoRR, 2017)

On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes. - Nguyen Tran Quang; Alexander Jung (CoRR, 2017)

When is Network Lasso Accurate: The Vector Case. - Nguyen Q. Tran; Saeed Basirian; Alexander Jung (CoRR, 2017)

A Fixed-Point of View on Gradient Methods for Big Data. - Alexander Jung (Frontiers Appl. Math. Stat., 2017)

When Is Network Lasso Accurate? - Alexander Jung; Nguyen Tran Quang; Alexandru Mara (Frontiers Appl. Math. Stat., 2017)

Classifying Big Data Over Networks Via The Logistic Network Lasso. - Henrik Ambos; Nguyen Q. Tran; Alexander Jung (ACSSC, 2018)

Classifying Process Instances Using Recurrent Neural Networks. - Markku Hinkka; Teemu Lehto; Keijo Heljanko; Alexander Jung (Business Process Management Workshops, 2018)

Predictive Maintenance of Photovoltaic Panels via Deep Learning. - Timo Huuhtanen; Alexander Jung (DSW, 2018)

Predicting Electricity Outages Caused By Convective Storms. - Roope Tervo; Joonas Karjalainen; Alexander Jung (DSW, 2018)

On the Sample Complexity of Graphical Model Selection from Non-Stationary Samples. - Nguyen Q. Tran; Alexander Jung (ICASSP, 2018)

Network Intrusion Detection Using Flow Statistics. - Buse Gul Atli; Yoan Miche; Alexander Jung (SSP, 2018)

A Network Compatibility Condition For Compressed Sensing Over Complex Networks. - Nguyen Q. Tran; Henrik Ambos; Alexander Jung (SSP, 2018)

Dynamic Clustering Scheme for Evolving Data Streams Based on Improved STRAP. - Jinping Sui; Zhen Liu 004; Alexander Jung; Li Liu 002; Xiang Li 014 (IEEE Access, 2018)

Online Feature Ranking for Intrusion Detection Systems. - Buse Gul Atli; Alexander Jung (CoRR, 2018)

The Logistic Network Lasso. - Henrik Ambos; Nguyen Q. Tran; Alexander Jung (CoRR, 2018)

A Gentle Introduction to Supervised Machine Learning. - Alexander Jung (CoRR, 2018)

Analysis of Network Lasso For Semi-Supervised Regression. - Alexander Jung (CoRR, 2018)

On the Complexity of Sparse Label Propagation. - Alexander Jung (Frontiers Appl. Math. Stat., 2018)

The Network Nullspace Property for Compressed Sensing of Big Data Over Networks. - Alexander Jung; Madelon Hulsebos (Frontiers Appl. Math. Stat., 2018)

Analysis of Network Lasso for Semi-Supervised Regression. - Alexander Jung; Natalia Vesselinova (AISTATS, 2019)

Outlier Detection from Non-Smooth Sensor Data. - Timo Huuhtanen; Henrik Ambos; Alexander Jung (EUSIPCO, 2019)

Systematic RISC-V based Firmware Design⋆. - Vladimir Herdt; Daniel Große; Rolf Drechsler; Christoph Gerum; Alexander Jung; Joscha Benz; Oliver Bringmann 001; Michael Schwarz 010; Dominik Stoffel; Wolfgang Kunz (FDL, 2019)

Graph Signal Sampling via Reinforcement Learning. - Oleksii Abramenko; Alexander Jung (ICASSP, 2019)

Sparse Subspace Clustering for Evolving Data Streams. - Jinping Sui; Zhen Liu 004; Li Liu 002; Alexander Jung; Tianpeng Liu; Bo Peng; Xiang Li 014 (ICASSP, 2019)

Automating Root Cause Analysis via Machine Learning in Agile Software Testing Environments. - Julen Kahles; Juha Torronen; Timo Huuhtanen; Alexander Jung (ICST, 2019)

Learning Networked Exponential Families with Network Lasso. - Alexander Jung (CoRR, 2019)

Components of Machine Learning: Binding Bits and FLOPS. - Alexander Jung (CoRR, 2019)

Basic Principles of Clustering Methods. - Alexander Jung; Ivan Baranov (CoRR, 2019)

The Actor-Dueling-Critic Method for Reinforcement Learning. - Menghao Wu; Yanbin Gao; Alexander Jung; Qiang Zhang; Shitong Du (Sensors, 2019)

Localized Linear Regression in Networked Data. - Alexander Jung; Nguyen Q. Tran (IEEE Signal Process. Lett., 2019)

Short-Term Prediction of Electricity Outages Caused by Convective Storms. - Roope Tervo; Joonas Karjalainen; Alexander Jung (IEEE Trans. Geosci. Remote. Sens., 2019)

Semi-Supervised Learning in Network-Structured Data via Total Variation Minimization. - Alexander Jung; Alfred O. Hero III; Alexandru Mara; Saeed Jahromi; Ayelet Heimowitz; Yonina C. Eldar (IEEE Trans. Signal Process., 2019)

Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization. - Alexander Jung (ACSSC, 2020)

Towards Highly Specialized, POSIX -compliant Software Stacks with Unikraft: Work-in-Progress. - Sharan Santhanam; Simon Kuenzer; Hugo Lefeuvre; Felipe Huici; Alexander Jung; Santiago Pagani; George-Cristian Muraru; Stefano Stabellini; Justin He; Jonathan Beri (EMSOFT, 2020)

Target Tracking on Sensing Surface with Electrical Impedance Tomography. - Timo Huuhtanen; Antti Lankinen; Alexander Jung (EUSIPCO, 2020)

Classifying Partially Labeled Networked Data VIA Logistic Network Lasso. - Nguyen Q. Tran; Henrik Ambos; Alexander Jung (ICASSP, 2020)

Anomaly Location Detection with Electrical Impedance Tomography Using Multilayer Perceptrons. - Timo Huuhtanen; Alexander Jung (MLSP, 2020)

Learning Explainable Decision Rules via Maximum Satisfiability. - Henrik E. C. Cao; Riku Sarlin; Alexander Jung (IEEE Access, 2020)

Networked Exponential Families for Big Data Over Networks. - Alexander Jung (IEEE Access, 2020)

Local Graph Clustering with Network Lasso. - Alexander Jung (CoRR, 2020)

Explainable Empirical Risk Minimization. - Alexander Jung (CoRR, 2020)

On the Duality Between Network Flows and Network Lasso. - Alexander Jung (IEEE Signal Process. Lett., 2020)

An Information-Theoretic Approach to Personalized Explainable Machine Learning. - Alexander Jung; Pedro H. J. Nardelli (IEEE Signal Process. Lett., 2020)

On the Sample Complexity of Graphical Model Selection From Non-Stationary Samples. - Nguyen Q. Tran; Oleksii Abramenko; Alexander Jung (IEEE Trans. Signal Process., 2020)

Flow-Based Clustering and Spectral Clustering: A Comparison. - Yasmin Sarcheshmehpour; Yu Tian; Linli Zhang; Alexander Jung (ACSCC, 2021)

Wayfinder: towards automatically deriving optimal OS configurations. - Alexander Jung; Hugo Lefeuvre; Charalampos Rotsos; Pierre Olivier; Daniel Oñoro-Rubio; Felipe Huici; Mathias Niepert (APSys, 2021)

Unikraft: fast, specialized unikernels the easy way. - 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; et al. (EuroSys, 2021)

Federated Learning from Big Data Over Networks. - Yasmin Sarcheshmehpour; M. Leinonen; Alexander Jung (ICASSP, 2021)

Networked Federated Multi-Task Learning. - Yasmin Sarcheshmehpour; Yu Tian; Linli Zhang; Alexander Jung (CoRR, 2021)

Rethinking Drone-Based Search and Rescue with Aerial Person Detection. - Pasi Pyrrö; Hassan Naseri; Alexander Jung (CoRR, 2021)

Containing Future Epidemics With Trustworthy Federated Systems for Ubiquitous Warning and Response. - Dick Carrillo; Lam Duc Nguyen; Pedro H. J. Nardelli; Evangelos Pournaras; Plinio P. Morita; Demóstenes Z. Rodríguez; Merim Dzaferagic; Harun Siljak; Alexander Jung; Laurent Hébert-Dufresne; Irene Macaluso; Mehar Ullah; et al. (Frontiers Commun. Networks, 2021)

Corrigendum: Containing Future Epidemics With Trustworthy Federated Systems for Ubiquitous Warning and Response. - Dick Carrillo; Lam Duc Nguyen; Pedro H. J. Nardelli; Evangelos Pournaras; Plinio P. Morita; Demóstenes Z. Rodríguez; Merim Dzaferagic; Harun Siljak; Alexander Jung; Laurent Hébert-Dufresne; Irene Macaluso; Mehar Ullah; et al. (Frontiers Commun. Networks, 2021)

Local Graph Clustering With Network Lasso. - Alexander Jung; Yasmin Sarcheshmehpour (IEEE Signal Process. Lett., 2021)

Machine Learning - The Basics - Alexander Jung (Springer, 2022)

FlexOS: towards flexible OS isolation. - Hugo Lefeuvre; Vlad-Andrei Badoiu; Alexander Jung; Stefan Lucian Teodorescu; Sebastian Rauch; Felipe Huici; Costin Raiciu; Pierre Olivier (ASPLOS, 2022)

Dynamic Sparse Subspace Clustering for Evolving High-Dimensional Data Streams. - Jinping Sui; Zhen Liu 004; Li Liu 002; Alexander Jung; Xiang Li 014 (IEEE Trans. Cybern., 2022)

Moreau Envelope ADMM for Decentralized Weakly Convex Optimization. - Reza Mirzaeifard; Naveen K. D. Venkategowda; Alexander Jung; Stefan Werner 001 (APSIPA ASC, 2023)

Towards Model-Agnostic Federated Learning over Networks. - Alexander Jung; S. Abdurakhmanova; Olga Kuznetsova; Yasmin Sarcheshmehpour (EUSIPCO, 2023)

Wind to start the washing machine? High-Resolution Wind Atlas for Finland. - Xu Yang; Yu Tian; Irene Schicker; Alexander Jung (CoRR, 2023)

Design of Induction Machines using Reinforcement Learning. - Yasmin Sarcheshmehpour; Tommi Ryyppo; Victor Mukherjee; Alex Jung (CoRR, 2023)

Hercules: Deep Hierarchical Attentive Multilevel Fusion Model With Uncertainty Quantification for Medical Image Classification. - Moloud Abdar; Mohammad Amin Fahami; Leonardo Rundo; Petia Radeva; Alejandro F. Frangi; U. Rajendra Acharya; Abbas Khosravi; Hak-Keung Lam; Alexander Jung; Saeid Nahavandi (IEEE Trans. Ind. Informatics, 2023)

Clustered Federated Learning via Generalized Total Variation Minimization. - Yasmin Sarcheshmehpour; Yu Tian; Linli Zhang; Alexander Jung (IEEE Trans. Signal Process., 2023)

Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology. - Argyrios Petras; Matthias A. F. Gsell; Christoph M. Augustin; Jairo Rodríguez-Padilla; Alexander Jung; Marina Strocchi; Frits W. Prinzen; Steven A. Niederer; Gernot Plank; Edward J. Vigmond (Comput. Biol. Medicine, 2023)

Opportunistic Protocols for People Counting in Dynamic Networks. - Alexander Jung; Helge Parzyjegla; Peter Danielis (CCNC, 2024)

Analysis of Total Variation Minimization for Clustered Federated Learning. - Alexander Jung (EUSIPCO, 2024)

Clustering students' text form feedback data: comparison of eight vector space models. - Wilhelmiina Hämäläinen; Jan-Mikael Rybicki; Lauri Malmi; Alex Jung; Kerttu Pollari-Malmi (ICBDE, 2024)

Inertia emulation contribution of Frades 2 variable speed pump-turbine to power network stability. - Christophe Nicolet; Antoine Béguin; Matthieu Dreyer; Sébastien Alligné; Alexander Jung; Diogo Cordeiro; Carlos Moreira (CoRR, 2024)

Personalized Federated Learning via Active Sampling. - Alexander Jung; Yasmin Sarcheshmehpour; Amirhossein Mohammadi (CoRR, 2024)

Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization. - Diana Pfau; Alexander Jung (CoRR, 2024)

Explainable empirical risk minimization. - Linli Zhang; Georgios Karakasidis; Arina Odnoblyudova; Leyla Dogruel; Yu Tian; Alex Jung (Neural Comput. Appl., 2024)

From intangible to tangible: The role of big data and machine learning in walkability studies. - Jun Yang; Pia Fricker; Alexander Jung (Comput. Environ. Urban Syst., 2024)

Datenschutzrechtliche Herausforderungen bei der Verwertung von Daten vernetzter Medizinprodukte. - Stefan Hessel; Alexander Jung (Datenschutz und Datensicherheit (dud), 2024)

Enforcing Fundamental Relations via Adversarial Attacks on Input Parameter Correlations. - Timo Saala; Lucie Flek; Alexander Jung; Akbar Karimi 001; Alexander Schmidt; Matthias Schott; Philipp Soldin; Christopher Wiebusch (CoRR, 2025)