Yanning Shen

IEEE Trans. Neural Networks Learn. Syst., September, 2024

FairGAT: Fairness-Aware Graph Attention Networks.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, August, 2024

Online Learning With Uncertain Feedback Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., July, 2024

Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Budgeted Online Model Selection and Fine-Tuning via Federated Learning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

FairViT: Fair Vision Transformer via Adaptive Masking.

[BibT_eX]

[DOI]

Bowei Tian

CoRR, 2024

TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks.

[BibT_eX]

[DOI]

Yezi Liu

CoRR, 2024

FairWire: Fair Graph Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Long-term Fairness For Real-time Decision Making: A Constrained Online Optimization Approach.

[BibT_eX]

[DOI]

Deepan Muthirayan

Pramod P. Khargonekar

CoRR, 2024

Filtering as Rewiring for Bias Mitigation on Graphs.

[BibT_eX]

[DOI]

Gonzalo Mateos

Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

TinyData: Joint Dataset Condensation with Dimensionality Reduction.

[BibT_eX]

[DOI]

Yezi Liu

Proceedings of the 32nd European Signal Processing Conference, 2024

2023

Multiple Kernel Representation Learning on Networks.

[BibT_eX]

[DOI]

Abdulkadir Çelikkanat

Fragkiskos D. Malliaros

IEEE Trans. Knowl. Data Eng., June, 2023

Fast&Fair: Training Acceleration and Bias Mitigation for GNNs.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Graph-Aided Online Multi-Kernel Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Fairness-aware Optimal Graph Filter Design.

[BibT_eX]

[DOI]

Gonzalo Mateos

CoRR, 2023

Fairness in Graph Machine Learning: Recent Advances and Future Prospectives.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Dynamic Fair Node Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Fairness-Aware Dimensionality Reduction.

[BibT_eX]

[DOI]

Proceedings of the 31st European Signal Processing Conference, 2023

Model Extraction Attacks Against Reinforcement Learning Based Controllers.

[BibT_eX]

[DOI]

Momina Sajid

Yasser Shoukry

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Change Point Detection Approach for Online Control of Unknown Time Varying Dynamical Systems.

[BibT_eX]

[DOI]

Deepan Muthirayan

Pramod P. Khargonekar

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Fairness-Aware Graph Filter Design.

[BibT_eX]

[DOI]

Gonzalo Mateos

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022

Fair Contrastive Learning on Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Inf. Process. over Networks, 2022

Adaptive Control of Unknown Time Varying Dynamical Systems with Regret Guarantees.

[BibT_eX]

[DOI]

Deepan Muthirayan

Pramod P. Khargonekar

CoRR, 2022

Explaining Dynamic Graph Neural Networks via Relevance Back-propagation.

[BibT_eX]

[DOI]

Jiaxuan Xie

Yezi Liu

CoRR, 2022

FairNorm: Fair and Fast Graph Neural Network Training.

[BibT_eX]

[DOI]

CoRR, 2022

Fair Node Representation Learning via Adaptive Data Augmentation.

[BibT_eX]

[DOI]

CoRR, 2022

Personalized Online Federated Learning with Multiple Kernels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fairness-Aware Selective Sampling on Attributed Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Online Learning with Probabilistic Feedback.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Fairness-aware Adaptive Network Link Prediction.

[BibT_eX]

[DOI]

Proceedings of the 30th European Signal Processing Conference, 2022

Graph-Assisted Communication-Efficient Ensemble Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the 30th European Signal Processing Conference, 2022

Fairness-aware User Classification in Power Grids.

[BibT_eX]

[DOI]

Proceedings of the 30th European Signal Processing Conference, 2022

Fairness-aware Graph Attention Networks.

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021

Distributed and Quantized Online Multi-Kernel Learning.

[BibT_eX]

[DOI]

Saeed Karimi-Bidhendi

Hamid Jafarkhani

IEEE Trans. Signal Process., 2021

Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network.

[BibT_eX]

[DOI]

CoRR, 2021

Fairness-Aware Node Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Online Multi-Hop Information Based Kernel Learning Over Graphs.

[BibT_eX]

[DOI]

Zixiao Zong

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Graph-Based Learning Under Perturbations via Total Least-Squares.

[BibT_eX]

[DOI]

Elena Ceci

Sergio Barbarossa

IEEE Trans. Signal Process., 2020

Topology Identification of Directed Graphs via Joint Diagonalization of Correlation Matrices.

[BibT_eX]

[DOI]

Xiao Fu

Nicholas D. Sidiropoulos

IEEE Trans. Signal Inf. Process. over Networks, 2020

Differentially Private Nonlinear Canonical Correlation Analysis.

[BibT_eX]

[DOI]

Proceedings of the 11th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020

Online Multi-Kernel Learning with Graph-Structured Feedback.

[BibT_eX]

[DOI]

Georgios Vasileios Karanikolas

Proceedings of the 37th International Conference on Machine Learning, 2020

Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability.

[BibT_eX]

[DOI]

Qin Lu

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Graph-aided Online Learning with Expert Advice.

[BibT_eX]

[DOI]

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

2019

Online Graph-Adaptive Learning With Scalability and Privacy.

[BibT_eX]

[DOI]

Geert Leus

IEEE Trans. Signal Process., 2019

Nonlinear Structural Vector Autoregressive Models With Application to Directed Brain Networks.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Semi-Blind Inference of Topologies and Dynamical Processes Over Dynamic Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2019

Scalable Learning with Privacy Over Graphs.

[BibT_eX]

[DOI]

Geert Leus

Proceedings of the IEEE Data Science Workshop, 2019

Scalable and Adaptive KNN for Regression Over Graphs.

[BibT_eX]

[DOI]

Seth Barrash

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018

Canonical Correlation Analysis of Datasets With a Common Source Graph.

[BibT_eX]

[DOI]

Jia Chen

Gang Wang

IEEE Trans. Signal Process., 2018

Topology Identification and Learning over Graphs: Accounting for Nonlinearities and Dynamics.

[BibT_eX]

[DOI]

Georgios Vasileios Karanikolas

Proc. IEEE, 2018

Heterogeneous Online Learning for "Thing-Adaptive" Fog Computing in IoT.

[BibT_eX]

[DOI]

Qing Ling

IEEE Internet Things J., 2018

Semi-Blind Inference of Topologies and Dynamical Processes over Graphs.

[BibT_eX]

[DOI]

CoRR, 2018

Canonical Correlation Analysis with Common Graph Priors.

[BibT_eX]

[DOI]

Jia Chen

Gang Wang

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Online Learning Adaptive to Dynamic and Adversarial Environments.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Kernel-Based Semi-Supervised Learning Over Multilayer Graphs.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Online Multi-Kernel Learning with Orthogonal Random Features.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Online Identification of Directional Graph Topologies Capturing Dynamic and Nonlinear Dependencies.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Data Science Workshop, 2018

Semi-Blind Inference of Topologies and Signals over Graphs.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Data Science Workshop, 2018

Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Signal and Graph Perturbations via Total Least-Squares.

[BibT_eX]

[DOI]

Elena Ceci

Sergio Barbarossa

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

2017

Online Categorical Subspace Learning for Sketching Big Data with Misses.

[BibT_eX]

[DOI]

Morteza Mardani

IEEE Trans. Signal Process., 2017

Tensor Decompositions for Identifying Directed Graph Topologies and Tracking Dynamic Networks.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2017

Kernel-Based Structural Equation Models for Topology Identification of Directed Networks.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2017

Topology inference of multilayer networks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Communications Workshops, 2017

Topology inference of directed graphs using nonlinear structural vector autoregressive models.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Network topology inference via elastic net structural equation models.

[BibT_eX]

[DOI]

Proceedings of the 25th European Signal Processing Conference, 2017

Nonlinear dimensionality reduction on graphs.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Directed network topology inference via sparse joint diagonalization.

[BibT_eX]

[DOI]

Xiao Fu

Nicholas D. Sidiropoulos

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

Online learning for "thing-adaptive" Fog Computing in IoT.

[BibT_eX]

[DOI]

Qing Ling

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

2016

Super-Resolution Compressed Sensing for Line Spectral Estimation: An Iterative Reweighted Approach.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2016

Adaptive one-bit quantization for compressed sensing.

[BibT_eX]

[DOI]

Signal Process., 2016

Tracking dynamic piecewise-constant network topologies via adaptive tensor factorization.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Online dictionary learning from large-scale binary data.

[BibT_eX]

[DOI]

Proceedings of the 24th European Signal Processing Conference, 2016

Nonlinear structural equation models for network topology inference.

[BibT_eX]

[DOI]

Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Inferring directed network topologies via tensor factorization.

[BibT_eX]

[DOI]

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

2015

Pattern-Coupled Sparse Bayesian Learning for Recovery of Block-Sparse Signals.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2015

Support knowledge-aided sparse Bayesian learning for compressed sensing.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Online sketching of big categorical data with absent features.

[BibT_eX]

[DOI]

Morteza Mardani

Proceedings of the 49th Annual Conference on Information Sciences and Systems, 2015

2014

Super-Resolution Compressed Sensing: An Iterative Reweighted Algorithm for Joint Parameter Learning and Sparse Signal Recovery.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2014

Sparse signal recovery from one-bit quantized data: An iterative reweighted algorithm.

[BibT_eX]

[DOI]

Signal Process., 2014

Prior Support Knowledge-Aided Sparse Bayesian Learning with Partly Erroneous Support Information.

[BibT_eX]

[DOI]

CoRR, 2014

Pattern coupled sparse Bayesian learning for recovery of time varying sparse signals.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Digital Signal Processing, 2014

Pattern-coupled sparse Bayesian learning for recovery of block-sparse signals.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Exact Reconstruction Analysis of Log-Sum Minimization for Compressed Sensing.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2013

One-Bit Quantization Design and Adaptive Methods for Compressed Sensing

[BibT_eX]

[DOI]

CoRR, 2013

A one-bit reweighted iterative algorithm for sparse signal recovery.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2013

One-bit compressive sensing and source localization in wireless sensor networks.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE China Summit and International Conference on Signal and Information Processing, 2013

2012

A Fast Iterative Algorithm for Recovery of Sparse Signals from One-Bit Quantized Measurements

[BibT_eX]

[DOI]