Yanning Shen

Orcid: 0000-0002-7333-893X

According to our database1, Yanning Shen authored at least 84 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

FairWire: Fair Graph Generation.
CoRR, 2024

Budgeted Online Model Selection and Fine-Tuning via Federated Learning.
CoRR, 2024

Long-term Fairness For Real-time Decision Making: A Constrained Online Optimization Approach.
CoRR, 2024

2023
Multiple Kernel Representation Learning on Networks.
IEEE Trans. Knowl. Data Eng., June, 2023

Fast&Fair: Training Acceleration and Bias Mitigation for GNNs.
Trans. Mach. Learn. Res., 2023

Graph-Aided Online Multi-Kernel Learning.
J. Mach. Learn. Res., 2023

Fairness-aware Optimal Graph Filter Design.
CoRR, 2023

FairGAT: Fairness-aware Graph Attention Networks.
CoRR, 2023

Fairness in Graph Machine Learning: Recent Advances and Future Prospectives.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Dynamic Fair Node Representation Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

Fairness-Aware Dimensionality Reduction.
Proceedings of the 31st European Signal Processing Conference, 2023

Model Extraction Attacks Against Reinforcement Learning Based Controllers.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Change Point Detection Approach for Online Control of Unknown Time Varying Dynamical Systems.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Fairness-Aware Graph Filter Design.
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.
IEEE Trans. Signal Inf. Process. over Networks, 2022

Adaptive Control of Unknown Time Varying Dynamical Systems with Regret Guarantees.
CoRR, 2022

Explaining Dynamic Graph Neural Networks via Relevance Back-propagation.
CoRR, 2022

FairNorm: Fair and Fast Graph Neural Network Training.
CoRR, 2022

Fair Node Representation Learning via Adaptive Data Augmentation.
CoRR, 2022

Personalized Online Federated Learning with Multiple Kernels.
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.
Proceedings of the IEEE International Conference on Acoustics, 2022

Online Learning with Probabilistic Feedback.
Proceedings of the IEEE International Conference on Acoustics, 2022

Fairness-aware Adaptive Network Link Prediction.
Proceedings of the 30th European Signal Processing Conference, 2022

Graph-Assisted Communication-Efficient Ensemble Federated Learning.
Proceedings of the 30th European Signal Processing Conference, 2022

Fairness-aware User Classification in Power Grids.
Proceedings of the 30th European Signal Processing Conference, 2022

Fairness-aware Graph Attention Networks.
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.
IEEE Trans. Signal Process., 2021

Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network.
CoRR, 2021

Online Learning with Uncertain Feedback Graphs.
CoRR, 2021

Fairness-Aware Node Representation Learning.
CoRR, 2021

Online Multi-Hop Information Based Kernel Learning Over Graphs.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Graph-Based Learning Under Perturbations via Total Least-Squares.
IEEE Trans. Signal Process., 2020

Topology Identification of Directed Graphs via Joint Diagonalization of Correlation Matrices.
IEEE Trans. Signal Inf. Process. over Networks, 2020

Differentially Private Nonlinear Canonical Correlation Analysis.
Proceedings of the 11th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020

Online Multi-Kernel Learning with Graph-Structured Feedback.
Proceedings of the 37th International Conference on Machine Learning, 2020

Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Graph-aided Online Learning with Expert Advice.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Online Graph-Adaptive Learning With Scalability and Privacy.
IEEE Trans. Signal Process., 2019

Nonlinear Structural Vector Autoregressive Models With Application to Directed Brain Networks.
IEEE Trans. Signal Process., 2019

Semi-Blind Inference of Topologies and Dynamical Processes Over Dynamic Graphs.
IEEE Trans. Signal Process., 2019

Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics.
J. Mach. Learn. Res., 2019

Scalable Learning with Privacy Over Graphs.
Proceedings of the IEEE Data Science Workshop, 2019

Scalable and Adaptive KNN for Regression Over Graphs.
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.
IEEE Trans. Signal Process., 2018

Topology Identification and Learning over Graphs: Accounting for Nonlinearities and Dynamics.
Proc. IEEE, 2018

Heterogeneous Online Learning for "Thing-Adaptive" Fog Computing in IoT.
IEEE Internet Things J., 2018

Semi-Blind Inference of Topologies and Dynamical Processes over Graphs.
CoRR, 2018

Canonical Correlation Analysis with Common Graph Priors.
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Online Learning Adaptive to Dynamic and Adversarial Environments.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Kernel-Based Semi-Supervised Learning Over Multilayer Graphs.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Online Multi-Kernel Learning with Orthogonal Random Features.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Online Identification of Directional Graph Topologies Capturing Dynamic and Nonlinear Dependencies.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Semi-Blind Inference of Topologies and Signals over Graphs.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Signal and Graph Perturbations via Total Least-Squares.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Online Categorical Subspace Learning for Sketching Big Data with Misses.
IEEE Trans. Signal Process., 2017

Tensor Decompositions for Identifying Directed Graph Topologies and Tracking Dynamic Networks.
IEEE Trans. Signal Process., 2017

Kernel-Based Structural Equation Models for Topology Identification of Directed Networks.
IEEE Trans. Signal Process., 2017

Topology inference of multilayer networks.
Proceedings of the 2017 IEEE Conference on Computer Communications Workshops, 2017

Topology inference of directed graphs using nonlinear structural vector autoregressive models.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Network topology inference via elastic net structural equation models.
Proceedings of the 25th European Signal Processing Conference, 2017

Nonlinear dimensionality reduction on graphs.
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.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

Online learning for "thing-adaptive" Fog Computing in IoT.
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.
IEEE Trans. Signal Process., 2016

Adaptive one-bit quantization for compressed sensing.
Signal Process., 2016

Tracking dynamic piecewise-constant network topologies via adaptive tensor factorization.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Online dictionary learning from large-scale binary data.
Proceedings of the 24th European Signal Processing Conference, 2016

Nonlinear structural equation models for network topology inference.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Inferring directed network topologies via tensor factorization.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Pattern-Coupled Sparse Bayesian Learning for Recovery of Block-Sparse Signals.
IEEE Trans. Signal Process., 2015

Support knowledge-aided sparse Bayesian learning for compressed sensing.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Online sketching of big categorical data with absent features.
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.
IEEE Signal Process. Lett., 2014

Sparse signal recovery from one-bit quantized data: An iterative reweighted algorithm.
Signal Process., 2014

Prior Support Knowledge-Aided Sparse Bayesian Learning with Partly Erroneous Support Information.
CoRR, 2014

Pattern coupled sparse Bayesian learning for recovery of time varying sparse signals.
Proceedings of the 19th International Conference on Digital Signal Processing, 2014

Pattern-coupled sparse Bayesian learning for recovery of block-sparse signals.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Exact Reconstruction Analysis of Log-Sum Minimization for Compressed Sensing.
IEEE Signal Process. Lett., 2013

One-Bit Quantization Design and Adaptive Methods for Compressed Sensing
CoRR, 2013

A one-bit reweighted iterative algorithm for sparse signal recovery.
Proceedings of the IEEE International Conference on Acoustics, 2013

One-bit compressive sensing and source localization in wireless sensor networks.
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
CoRR, 2012


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