Alexander Jung

114 papers A 2B 1Misc 18Journal 75Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Interpretable Multiple Myeloma Prognosis with Observational Medical Outcomes Partnership Data. CoRR Salma Rachidi, Aso Bozorgpanah, Eric Fey, Alexander Jung
2024	—	`conf`	Analysis of Total Variation Minimization for Clustered Federated Learning. EUSIPCO Alexander Jung
2024	J	`jnl`	Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization. CoRR Diana Pfau, Alexander Jung
2024	J	`jnl`	From intangible to tangible: The role of big data and machine learning in walkability studies. Comput. Environ. Urban Syst. Jun Yang, Pia Fricker, Alexander Jung
2024	J	`jnl`	Personalized Federated Learning via Active Sampling. CoRR Alexander Jung, Yasmin Sarcheshmehpour, Amirhossein Mohammadi
2023	J	`jnl`	Clustered Federated Learning via Generalized Total Variation Minimization. IEEE Trans. Signal Process. Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang, Alexander Jung
2023	J	`jnl`	Hercules: Deep Hierarchical Attentive Multilevel Fusion Model With Uncertainty Quantification for Medical Image Classification. IEEE Trans. Ind. Informatics Moloud Abdar, Mohammad Amin Fahami, Leonardo Rundo, Petia Radeva, Alejandro F. Frangi, U. Rajendra Acharya, Abbas Khosravi, Hak-Keung Lam, Alexander Jung, Saeid Nahavandi
2023	—	`conf`	Moreau Envelope ADMM for Decentralized Weakly Convex Optimization. APSIPA ASC Reza Mirzaeifard, Naveen K. D. Venkategowda, Alexander Jung, Stefan Werner
2023	J	`jnl`	Moreau Envelope ADMM for Decentralized Weakly Convex Optimization. CoRR Reza Mirzaeifard, Naveen K. D. Venkategowda, Alexander Jung, Stefan Werner
2023	—	`conf`	Towards Model-Agnostic Federated Learning over Networks. EUSIPCO Alexander Jung, S. Abdurakhmanova, Olga Kuznetsova, Yasmin Sarcheshmehpour
2023	J	`jnl`	Wind to start the washing machine? High-Resolution Wind Atlas for Finland. CoRR Xu Yang, Yu Tian, Irene Schicker, Alexander Jung
2022	J	`jnl`	Dynamic Sparse Subspace Clustering for Evolving High-Dimensional Data Streams. IEEE Trans. Cybern. Jinping Sui, Zhen Liu, Li Liu, Alexander Jung, Xiang Li
2022	—	`book`	Machine Learning - The Basics Alexander Jung
2022	J	`jnl`	flow-based clustering and spectral clustering: a comparison. CoRR Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang, Alexander Jung
2021	J	`jnl`	Containing Future Epidemics With Trustworthy Federated Systems for Ubiquitous Warning and Response. Frontiers Commun. Networks 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, Gustavo Fraidenraich, Petar Popovski
2021	J	`jnl`	Corrigendum: Containing Future Epidemics With Trustworthy Federated Systems for Ubiquitous Warning and Response. Frontiers Commun. Networks 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, Gustavo Fraidenraich, Petar Popovski
2021	Misc	`conf`	Federated Learning from Big Data Over Networks. ICASSP Yasmin Sarcheshmehpour, M. Leinonen, Alexander Jung
2021	—	`conf`	Flow-Based Clustering and Spectral Clustering: A Comparison. ACSCC Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang, Alexander Jung
2021	J	`jnl`	Local Graph Clustering With Network Lasso. IEEE Signal Process. Lett. Alexander Jung, Yasmin Sarcheshmehpour
2021	J	`jnl`	Networked Federated Multi-Task Learning. CoRR Yasmin Sarcheshmehpour, Yu Tian, Linli Zhang, Alexander Jung
2021	J	`jnl`	Rethinking Drone-Based Search and Rescue with Aerial Person Detection. CoRR Pasi Pyrrö, Hassan Naseri, Alexander Jung
2020	J	`jnl`	An Information-Theoretic Approach to Personalized Explainable Machine Learning. CoRR Alexander Jung, Pedro H. J. Nardelli
2020	J	`jnl`	An Information-Theoretic Approach to Personalized Explainable Machine Learning. IEEE Signal Process. Lett. Alexander Jung, Pedro H. J. Nardelli
2020	—	`conf`	Anomaly Location Detection with Electrical Impedance Tomography Using Multilayer Perceptrons. MLSP Timo Huuhtanen, Alexander Jung
2020	Misc	`conf`	Classifying Partially Labeled Networked Data VIA Logistic Network Lasso. ICASSP Nguyen Q. Tran, Henrik Ambos, Alexander Jung
2020	Misc	`conf`	Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization. ACSSC Alexander Jung
2020	J	`jnl`	Containing Future Epidemics with Trustworthy Federated Systems for Ubiquitous Warning and Response. CoRR 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, Gustavo Fraidenraich, Petar Popovski
2020	J	`jnl`	Explainable Empirical Risk Minimization. CoRR Alexander Jung
2020	J	`jnl`	Federated Learning From Big Data Over Networks. CoRR Yasmin Sarcheshmehpour, M. Leinonen, Alexander Jung
2020	J	`jnl`	Learning Explainable Decision Rules via Maximum Satisfiability. IEEE Access Henrik E. C. Cao, Riku Sarlin, Alexander Jung
2020	J	`jnl`	Local Graph Clustering with Network Lasso. CoRR Alexander Jung
2020	J	`jnl`	Networked Exponential Families for Big Data Over Networks. IEEE Access Alexander Jung
2020	J	`jnl`	On the Duality Between Network Flows and Network Lasso. IEEE Signal Process. Lett. Alexander Jung
2020	J	`jnl`	On the Sample Complexity of Graphical Model Selection From Non-Stationary Samples. IEEE Trans. Signal Process. Nguyen Q. Tran, Oleksii Abramenko, Alexander Jung
2020	—	`conf`	Target Tracking on Sensing Surface with Electrical Impedance Tomography. EUSIPCO Timo Huuhtanen, Antti Lankinen, Alexander Jung
2019	A	`conf`	Analysis of Network Lasso for Semi-Supervised Regression. AISTATS Alexander Jung, Natalia Vesselinova
2019	A	`conf`	Automating Root Cause Analysis via Machine Learning in Agile Software Testing Environments. ICST Julen Kahles, Juha Torronen, Timo Huuhtanen, Alexander Jung
2019	J	`jnl`	Basic Principles of Clustering Methods. CoRR Alexander Jung, Ivan Baranov
2019	J	`jnl`	Classifying Partially Labeled Networked Data via Logistic Network Lasso. CoRR Nguyen Q. Tran, Henrik Ambos, Alexander Jung
2019	J	`jnl`	Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization. CoRR Alexander Jung
2019	J	`jnl`	Components of Machine Learning: Binding Bits and FLOPS. CoRR Alexander Jung
2019	Misc	`conf`	Graph Signal Sampling via Reinforcement Learning. ICASSP Oleksii Abramenko, Alexander Jung
2019	J	`jnl`	Learning Networked Exponential Families with Network Lasso. CoRR Alexander Jung
2019	J	`jnl`	Localized Linear Regression in Networked Data. CoRR Alexander Jung, Nguyen Q. Tran
2019	J	`jnl`	Localized Linear Regression in Networked Data. IEEE Signal Process. Lett. Alexander Jung, Nguyen Q. Tran
2019	J	`jnl`	On the Duality between Network Flows and Network Lasso. CoRR Alexander Jung
2019	—	`conf`	Outlier Detection from Non-Smooth Sensor Data. EUSIPCO Timo Huuhtanen, Henrik Ambos, Alexander Jung
2019	J	`jnl`	Semi-Supervised Learning in Network-Structured Data via Total Variation Minimization. IEEE Trans. Signal Process. Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi, Ayelet Heimowitz, Yonina C. Eldar
2019	J	`jnl`	Semi-supervised Learning in Network-Structured Data via Total Variation Minimization. CoRR Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi, Ayelet Heimowitz, Yonina C. Eldar
2019	J	`jnl`	Short-Term Prediction of Electricity Outages Caused by Convective Storms. IEEE Trans. Geosci. Remote. Sens. Roope Tervo, Joonas Karjalainen, Alexander Jung
2019	J	`jnl`	Short-term prediction of Electricity Outages Caused by Convective Storms. CoRR Roope Tervo, Joonas Karjalainen, Alexander Jung
2019	Misc	`conf`	Sparse Subspace Clustering for Evolving Data Streams. ICASSP Jinping Sui, Zhen Liu, Li Liu, Alexander Jung, Tianpeng Liu, Bo Peng, Xiang Li
2019	J	`jnl`	The Actor-Dueling-Critic Method for Reinforcement Learning. Sensors Menghao Wu, Yanbin Gao, Alexander Jung, Qiang Zhang, Shitong Du
2018	J	`jnl`	A Gentle Introduction to Supervised Machine Learning. CoRR Alexander Jung
2018	—	`conf`	A Network Compatibility Condition For Compressed Sensing Over Complex Networks. SSP Nguyen Q. Tran, Henrik Ambos, Alexander Jung
2018	J	`jnl`	Analysis of Network Lasso For Semi-Supervised Regression. CoRR Alexander Jung
2018	Misc	`conf`	Classifying Big Data Over Networks Via The Logistic Network Lasso. ACSSC Henrik Ambos, Nguyen Q. Tran, Alexander Jung
2018	—	`conf`	Classifying Process Instances Using Recurrent Neural Networks. Business Process Management Workshops Markku Hinkka, Teemu Lehto, Keijo Heljanko, Alexander Jung
2018	J	`jnl`	Classifying Process Instances Using Recurrent Neural Networks. CoRR Markku Hinkka, Teemu Lehto, Keijo Heljanko, Alexander Jung
2018	J	`jnl`	Dynamic Clustering Scheme for Evolving Data Streams Based on Improved STRAP. IEEE Access Jinping Sui, Zhen Liu, Alexander Jung, Li Liu, Xiang Li
2018	J	`jnl`	Graph Signal Sampling via Reinforcement Learning. CoRR Oleksii Abramenko, Alexander Jung
2018	—	`conf`	Network Intrusion Detection Using Flow Statistics. SSP Buse Gul Atli, Yoan Miche, Alexander Jung
2018	J	`jnl`	On The Complexity of Sparse Label Propagation. CoRR Alexander Jung
2018	J	`jnl`	On the Complexity of Sparse Label Propagation. Frontiers Appl. Math. Stat. Alexander Jung
2018	Misc	`conf`	On the Sample Complexity of Graphical Model Selection from Non-Stationary Samples. ICASSP Nguyen Q. Tran, Alexander Jung
2018	J	`jnl`	Online Feature Ranking for Intrusion Detection Systems. CoRR Buse Gul Atli, Alexander Jung
2018	—	`conf`	Predicting Electricity Outages Caused By Convective Storms. DSW Roope Tervo, Joonas Karjalainen, Alexander Jung
2018	J	`jnl`	Predicting Electricity Outages Caused by Convective Storms. CoRR Roope Tervo, Joonas Karjalainen, Alexander Jung
2018	—	`conf`	Predictive Maintenance of Photovoltaic Panels via Deep Learning. DSW Timo Huuhtanen, Alexander Jung
2018	J	`jnl`	The Logistic Network Lasso. CoRR Henrik Ambos, Nguyen Q. Tran, Alexander Jung
2018	Misc	`conf`	The Network Nullspace Property for Compressed Sensing of Big Data Over Networks. ICASSP Madelon Hulsebos, Alexander Jung
2018	J	`jnl`	The Network Nullspace Property for Compressed Sensing of Big Data Over Networks. Frontiers Appl. Math. Stat. Alexander Jung, Madelon Hulsebos
2017	J	`jnl`	A Fixed-Point of View on Gradient Methods for Big Data. Frontiers Appl. Math. Stat. Alexander Jung
2017	Misc	`conf`	Domain Adaptation for Resume Classification Using Convolutional Neural Networks. AIST Luiza Sayfullina, Eric Malmi, Yiping Liao, Alexander Jung
2017	Misc	`conf`	Learning conditional independence structure for high-dimensional uncorrelated vector processes. ICASSP Nguyen Tran Quang, Alexander Jung
2017	J	`jnl`	On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes. CoRR Nguyen Tran Quang, Alexander Jung
2017	J	`jnl`	Random Walk Sampling for Big Data over Networks. CoRR Saeed Basirian, Alexander Jung
2017	J	`jnl`	Recovery Conditions and Sampling Strategies for Network Lasso. CoRR Alexandru Mara, Alexander Jung
2017	Misc	`conf`	Recovery conditions and sampling strategies for network Lasso. ACSSC Alexandru Mara, Alexander Jung
2017	Misc	`conf`	Smooth graph signal recovery via efficient Laplacian solvers. ICASSP Gita Babazadeh Eslamlou, Alexander Jung, Norbert Goertz
2017	—	`conf`	Structural Feature Selection for Event Logs. Business Process Management Workshops Markku Hinkka, Teemu Lehto, Keijo Heljanko, Alexander Jung
2017	J	`jnl`	Structural Feature Selection for Event Logs. CoRR Markku Hinkka, Teemu Lehto, Keijo Heljanko, Alexander Jung
2017	J	`jnl`	The Network Nullspace Property for Compressed Sensing of Big Data over Networks. CoRR Alexander Jung
2017	J	`jnl`	When Is Network Lasso Accurate? Frontiers Appl. Math. Stat. Alexander Jung, Nguyen Tran Quang, Alexandru Mara
2017	J	`jnl`	When is Network Lasso Accurate: The Vector Case. CoRR Nguyen Q. Tran, Saeed Basirian, Alexander Jung
2016	J	`jnl`	Big Data Frameworks: A Comparative Study. CoRR Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Alexander Jung
2016	Misc	`conf`	Efficient graph signal recovery over big networks. ACSSC Gabor Hannak, Peter Berger, Gerald Matz, Alexander Jung
2016	Misc	`conf`	Graph signal recovery from incomplete and noisy information using approximate message passing. ICASSP Gita Babazadeh Eslamlou, Alexander Jung, Norbert Goertz, Mehdi Fereydooni
2016	J	`jnl`	Learning conditional independence structure for high-dimensional uncorrelated vector processes. CoRR Nguyen Tran Quang, Alexander Jung
2016	J	`jnl`	On the Minimax Risk of Dictionary Learning. IEEE Trans. Inf. Theory Alexander Jung, Yonina C. Eldar, Norbert Goertz
2016	J	`jnl`	Scalable Semi-Supervised Learning over Networks using Nonsmooth Convex Optimization. CoRR Alexander Jung, Alfred O. Hero III, Alexandru Mara, Sabeur Aridhi
2016	—	`conf`	Scalable graph signal recovery for big data over networks. SPAWC Alexander Jung, Peter Berger, Gabor Hannak, Gerald Matz
2016	J	`jnl`	Sparse Label Propagation. CoRR Alexander Jung
2015	J	`jnl`	Graphical LASSO based Model Selection for Time Series. IEEE Signal Process. Lett. Alexander Jung, Gabor Hannak, Norbert Goertz
2015	—	`conf`	Joint channel estimation and activity detection for multiuser communication systems. ICC Workshops Gabor Hannak, Martin Mayer, Alexander Jung, Gerald Matz, Norbert Goertz
2015	J	`jnl`	Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach. IEEE Trans. Signal Process. Alexander Jung
2015	J	`jnl`	On the Minimax Risk of Dictionary Learning. CoRR Alexander Jung, Yonina C. Eldar, Norbert Görtz
2014	Misc	`conf`	Compressive nonparametric graphical model selection for time series. ICASSP Alexander Jung, Reinhard Heckel, Helmut Bölcskei, Franz Hlawatsch
2014	J	`jnl`	Iterative Recovery of Dense Signals from Incomplete Measurements. IEEE Signal Process. Lett. Norbert Goertz, Chunli Guo, Alexander Jung, Mike E. Davies, Gerhard Doblinger
2014	J	`jnl`	Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An RKHS Approach. IEEE Trans. Inf. Theory Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch, Zvika Ben-Haim, Yonina C. Eldar
2014	—	`conf`	On the information-theoretic limits of graphical model selection for Gaussian time series. EUSIPCO Gabor Hannak, Alexander Jung, Norbert Goertz
2014	—	`conf`	Performance limits of dictionary learning for sparse coding. EUSIPCO Alexander Jung, Yonina C. Eldar, Norbert Goertz
2014	J	`jnl`	The RKHS Approach to Minimum Variance Estimation Revisited: Variance Bounds, Sufficient Statistics, and Exponential Families. IEEE Trans. Inf. Theory Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch
2013	J	`jnl`	Compressive Spectral Estimation for Nonstationary Random Processes. IEEE Trans. Inf. Theory Alexander Jung, Georg Tauböck, Franz Hlawatsch
2013	J	`jnl`	Minimum Variance Estimation of a Sparse Vector within the Linear Gaussian Model: An RKHS Approach CoRR Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch, Zvika Ben-Haim, Yonina C. Eldar
2011	B	`conf`	Minimum variance estimation for the sparse signal in noise model. ISIT Sebastian Schmutzhard, Alexander Jung, Franz Hlawatsch
2011	J	`jnl`	Performance Bounds for Sparse Parametric Covariance Estimation in Gaussian Models CoRR Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch, Alfred O. Hero III
2011	Misc	`conf`	Performance bounds for sparse parametric covariance estimation in Gaussian models. ICASSP Alexander Jung, Sebastian Schmutzhard, Franz Hlawatsch, Alfred O. Hero III
2011	J	`jnl`	Unbiased Estimation of a Sparse Vector in White Gaussian Noise. IEEE Trans. Inf. Theory Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Yonina C. Eldar
2010	J	`jnl`	A Lower Bound on the Estimator Variance for the Sparse Linear Model CoRR Sebastian Schmutzhard, Alexander Jung, Franz Hlawatsch, Zvika Ben-Haim, Yonina C. Eldar
2010	J	`jnl`	On Unbiased Estimation of Sparse Vectors Corrupted by Gaussian Noise CoRR Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Yonina C. Eldar
2010	Misc	`conf`	On unbiased estimation of sparse vectors corrupted by Gaussian noise. ICASSP Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Yonina C. Eldar
2010	J	`jnl`	Unbiased Estimation of a Sparse Vector in White Gaussian Noise. CoRR Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Yonina C. Eldar
2009	Misc	`conf`	Compressive spectral estimation for nonstationary random processes. ICASSP Alexander Jung, Georg Tauböck, Franz Hlawatsch