Alexander Jung

Springer, ISBN: 978-981-16-8192-9, 2022

2021

Local Graph Clustering With Network Lasso.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2021

Rethinking Drone-Based Search and Rescue with Aerial Person Detection.

[BibT_eX]

[DOI]

Pasi Pyrrö

Hassan Naseri

CoRR, 2021

Networked Federated Multi-Task Learning.

[BibT_eX]

[DOI]

Yu Tian

Linli Zhang

CoRR, 2021

Federated Learning from Big Data Over Networks.

[BibT_eX]

[DOI]

M. Leinonen

Proceedings of the IEEE International Conference on Acoustics, 2021

Unikraft: fast, specialized unikernels the easy way.

[BibT_eX]

[DOI]

Proceedings of the EuroSys '21: Sixteenth European Conference on Computer Systems, 2021

Wayfinder: towards automatically deriving optimal OS configurations.

[BibT_eX]

[DOI]

Proceedings of the APSys '21: 12th ACM SIGOPS Asia-Pacific Workshop on Systems, 2021

Flow-Based Clustering and Spectral Clustering: A Comparison.

[BibT_eX]

[DOI]

Yu Tian

Linli Zhang

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

On the Sample Complexity of Graphical Model Selection From Non-Stationary Samples.

[BibT_eX]

[DOI]

Oleksii Abramenko

IEEE Trans. Signal Process., 2020

An Information-Theoretic Approach to Personalized Explainable Machine Learning.

[BibT_eX]

[DOI]

Pedro H. J. Nardelli

IEEE Signal Process. Lett., 2020

On the Duality Between Network Flows and Network Lasso.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2020

Containing Future Epidemics with Trustworthy Federated Systems for Ubiquitous Warning and Response.

[BibT_eX]

[DOI]

Demóstenes Z. Rodríguez

Merim Dzaferagic

Harun Siljak

Laurent Hébert-Dufresne

CoRR, 2020

Explainable Empirical Risk Minimization.

[BibT_eX]

[DOI]

CoRR, 2020

Local Graph Clustering with Network Lasso.

[BibT_eX]

[DOI]

CoRR, 2020

Networked Exponential Families for Big Data Over Networks.

[BibT_eX]

[DOI]

IEEE Access, 2020

Learning Explainable Decision Rules via Maximum Satisfiability.

[BibT_eX]

[DOI]

Henrik E. C. Cao

Riku Sarlin

IEEE Access, 2020

Anomaly Location Detection with Electrical Impedance Tomography Using Multilayer Perceptrons.

[BibT_eX]

[DOI]

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Classifying Partially Labeled Networked Data VIA Logistic Network Lasso.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Target Tracking on Sensing Surface with Electrical Impedance Tomography.

[BibT_eX]

[DOI]

Antti Lankinen

Proceedings of the 28th European Signal Processing Conference, 2020

Towards Highly Specialized, POSIX -compliant Software Stacks with Unikraft: Work-in-Progress.

[BibT_eX]

[DOI]

George-Cristian Muraru

Stefano Stabellini

Justin He

Jonathan Beri

Proceedings of the 20th International Conference on Embedded Software, 2020

Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization.

[BibT_eX]

[DOI]

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Semi-Supervised Learning in Network-Structured Data via Total Variation Minimization.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Short-Term Prediction of Electricity Outages Caused by Convective Storms.

[BibT_eX]

[DOI]

Roope Tervo

Joonas Karjalainen

IEEE Trans. Geosci. Remote. Sens., 2019

Localized Linear Regression in Networked Data.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2019

The Actor-Dueling-Critic Method for Reinforcement Learning.

[BibT_eX]

[DOI]

Sensors, 2019

Basic Principles of Clustering Methods.

[BibT_eX]

[DOI]

Ivan Baranov

CoRR, 2019

Components of Machine Learning: Binding Bits and FLOPS.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Networked Exponential Families with Network Lasso.

[BibT_eX]

[DOI]

CoRR, 2019

Automating Root Cause Analysis via Machine Learning in Agile Software Testing Environments.

[BibT_eX]

[DOI]

Proceedings of the 12th IEEE Conference on Software Testing, Validation and Verification, 2019

Sparse Subspace Clustering for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2019

Graph Signal Sampling via Reinforcement Learning.

[BibT_eX]

[DOI]

Oleksii Abramenko

Proceedings of the IEEE International Conference on Acoustics, 2019

Systematic RISC-V based Firmware Design<sup>⋆</sup>.

[BibT_eX]

[DOI]

Proceedings of the 2019 Forum for Specification and Design Languages, 2019

Outlier Detection from Non-Smooth Sensor Data.

[BibT_eX]

[DOI]

Proceedings of the 27th European Signal Processing Conference, 2019

Analysis of Network Lasso for Semi-Supervised Regression.

[BibT_eX]

[DOI]

Natalia Vesselinova

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

The Network Nullspace Property for Compressed Sensing of Big Data Over Networks.

[BibT_eX]

[DOI]

Madelon Hulsebos

Frontiers Appl. Math. Stat., 2018

On the Complexity of Sparse Label Propagation.

[BibT_eX]

[DOI]

Frontiers Appl. Math. Stat., 2018

Analysis of Network Lasso For Semi-Supervised Regression.

[BibT_eX]

[DOI]

CoRR, 2018

A Gentle Introduction to Supervised Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2018

The Logistic Network Lasso.

[BibT_eX]

[DOI]

CoRR, 2018

Online Feature Ranking for Intrusion Detection Systems.

[BibT_eX]

[DOI]

Buse Gul Atli

CoRR, 2018

Dynamic Clustering Scheme for Evolving Data Streams Based on Improved STRAP.

[BibT_eX]

[DOI]

IEEE Access, 2018

A Network Compatibility Condition For Compressed Sensing Over Complex Networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Network Intrusion Detection Using Flow Statistics.

[BibT_eX]

[DOI]

Buse Gul Atli

Yoan Miche

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

On the Sample Complexity of Graphical Model Selection from Non-Stationary Samples.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Predicting Electricity Outages Caused By Convective Storms.

[BibT_eX]

[DOI]

Roope Tervo

Joonas Karjalainen

Proceedings of the 2018 IEEE Data Science Workshop, 2018

Predictive Maintenance of Photovoltaic Panels via Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Data Science Workshop, 2018

Classifying Process Instances Using Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2018

Classifying Big Data Over Networks Via The Logistic Network Lasso.

[BibT_eX]

[DOI]

Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017

When Is Network Lasso Accurate?

[BibT_eX]

[DOI]

Nguyen Tran Quang

Alexandru Mara

Frontiers Appl. Math. Stat., 2017

A Fixed-Point of View on Gradient Methods for Big Data.

[BibT_eX]

[DOI]

Frontiers Appl. Math. Stat., 2017

When is Network Lasso Accurate: The Vector Case.

[BibT_eX]

[DOI]

Saeed Basirian

CoRR, 2017

On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes.

[BibT_eX]

[DOI]

Nguyen Tran Quang

CoRR, 2017

The Network Nullspace Property for Compressed Sensing of Big Data over Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Random Walk Sampling for Big Data over Networks.

[BibT_eX]

[DOI]

Saeed Basirian

CoRR, 2017

Learning conditional independence structure for high-dimensional uncorrelated vector processes.

[BibT_eX]

[DOI]

Nguyen Tran Quang

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Smooth graph signal recovery via efficient Laplacian solvers.

[BibT_eX]

[DOI]

Gita Babazadeh Eslamlou

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Differential SART for sub-Nyquist tomographic reconstruction in presence of misalignments.

[BibT_eX]

[DOI]

Proceedings of the 25th European Signal Processing Conference, 2017

Structural Feature Selection for Event Logs.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2017

Domain Adaptation for Resume Classification Using Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Analysis of Images, Social Networks and Texts, 2017

Recovery conditions and sampling strategies for network Lasso.

[BibT_eX]

[DOI]

Alexandru Mara

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

On the Minimax Risk of Dictionary Learning.

[BibT_eX]

[DOI]

Yonina C. Eldar

IEEE Trans. Inf. Theory, 2016

Scalable Semi-Supervised Learning over Networks using Nonsmooth Convex Optimization.

[BibT_eX]

[DOI]

CoRR, 2016

Sparse Label Propagation.

[BibT_eX]

[DOI]

CoRR, 2016

Big Data Frameworks: A Comparative Study.

[BibT_eX]

[DOI]

CoRR, 2016

Scalable graph signal recovery for big data over networks.

[BibT_eX]

[DOI]

Proceedings of the 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2016

Graph signal recovery from incomplete and noisy information using approximate message passing.

[BibT_eX]

[DOI]

Gita Babazadeh Eslamlou

Mehdi Fereydooni

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Efficient graph signal recovery over big networks.

[BibT_eX]

[DOI]

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2015

Graphical LASSO based Model Selection for Time Series.

[BibT_eX]

[DOI]

Gabor Hannak

IEEE Signal Process. Lett., 2015

Joint channel estimation and activity detection for multiuser communication systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communication, 2015

2014

Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An RKHS Approach.

[BibT_eX]

[DOI]

Zvika Ben-Haim

Yonina C. Eldar

IEEE Trans. Inf. Theory, 2014

The RKHS Approach to Minimum Variance Estimation Revisited: Variance Bounds, Sufficient Statistics, and Exponential Families.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2014

Iterative Recovery of Dense Signals from Incomplete Measurements.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2014

Compressive nonparametric graphical model selection for time series.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2014

Performance limits of dictionary learning for sparse coding.

[BibT_eX]

[DOI]

Yonina C. Eldar

Proceedings of the 22nd European Signal Processing Conference, 2014

On the information-theoretic limits of graphical model selection for Gaussian time series.

[BibT_eX]

[DOI]

Gabor Hannak

Proceedings of the 22nd European Signal Processing Conference, 2014

2013

Compressive Spectral Estimation for Nonstationary Random Processes.

[BibT_eX]

[DOI]

Georg Tauböck

IEEE Trans. Inf. Theory, 2013

2011

Unbiased Estimation of a Sparse Vector in White Gaussian Noise.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2011

Minimum variance estimation for the sparse signal in noise model.

[BibT_eX]

[DOI]

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Performance bounds for sparse parametric covariance estimation in Gaussian models.

[BibT_eX]

[DOI]

Alfred O. Hero III

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

A Lower Bound on the Estimator Variance for the Sparse Linear Model

[BibT_eX]

[DOI]