A Fast Iterative Algorithm for Recovery of Sparse Signals from One-Bit Quantized Measurements - Jun Fang 001; Yanning Shen; Hongbin Li 001 (CoRR, 2012)

One-bit compressive sensing and source localization in wireless sensor networks. - Yanning Shen; Jun Fang 001; Hongbin Li 001 (ChinaSIP, 2013)

A one-bit reweighted iterative algorithm for sparse signal recovery. - Yanning Shen; Jun Fang 001; Hongbin Li 001; Zhi Chen 002 (ICASSP, 2013)

One-Bit Quantization Design and Adaptive Methods for Compressed Sensing - Jun Fang 001; Yanning Shen; Huiping Duan; Hongbin Li 001 (CoRR, 2013)

Exact Reconstruction Analysis of Log-Sum Minimization for Compressed Sensing. - Yanning Shen; Jun Fang 001; Hongbin Li 001 (IEEE Signal Process. Lett., 2013)

Pattern-coupled sparse Bayesian learning for recovery of block-sparse signals. - Yanning Shen; Huiping Duan; Jun Fang 001; Hongbin Li 001 (ICASSP, 2014)

Pattern coupled sparse Bayesian learning for recovery of time varying sparse signals. - Jun Fang 001; Yanning Shen; Hongbin Li 001 (DSP, 2014)

Prior Support Knowledge-Aided Sparse Bayesian Learning with Partly Erroneous Support Information. - Jun Fang 001; Yanning Shen; Fuwei Li; Hongbin Li 001 (CoRR, 2014)

Sparse signal recovery from one-bit quantized data: An iterative reweighted algorithm. - Jun Fang 001; Yanning Shen; Hongbin Li 001; Zhi Ren 001 (Signal Process., 2014)

Super-Resolution Compressed Sensing: An Iterative Reweighted Algorithm for Joint Parameter Learning and Sparse Signal Recovery. - Jun Fang 001; Jing Li 066; Yanning Shen; Hongbin Li 001; Shaoqian Li (IEEE Signal Process. Lett., 2014)

Online sketching of big categorical data with absent features. - Yanning Shen; Morteza Mardani; Georgios B. Giannakis (CISS, 2015)

Support knowledge-aided sparse Bayesian learning for compressed sensing. - Jun Fang 001; Yanning Shen; Fuwei Li; Hongbin Li 001; Zhi Chen 002 (ICASSP, 2015)

Pattern-Coupled Sparse Bayesian Learning for Recovery of Block-Sparse Signals. - Jun Fang 001; Yanning Shen; Hongbin Li 001; Pu Wang 004 (IEEE Trans. Signal Process., 2015)

Inferring directed network topologies via tensor factorization. - Yanning Shen; Brian Baingana; Georgios B. Giannakis (ACSSC, 2016)

Nonlinear structural equation models for network topology inference. - Yanning Shen; Brian Baingana; Georgios B. Giannakis (CISS, 2016)

Online dictionary learning from large-scale binary data. - Yanning Shen; Georgios B. Giannakis (EUSIPCO, 2016)

Tracking dynamic piecewise-constant network topologies via adaptive tensor factorization. - Yanning Shen; Brian Baingana; Georgios B. Giannakis (GlobalSIP, 2016)

Adaptive one-bit quantization for compressed sensing. - Jun Fang 001; Yanning Shen; Linxiao Yang; Hongbin Li 001 (Signal Process., 2016)

Super-Resolution Compressed Sensing for Line Spectral Estimation: An Iterative Reweighted Approach. - Jun Fang 001; Feiyu Wang 001; Yanning Shen; Hongbin Li 001; Rick S. Blum (IEEE Trans. Signal Process., 2016)

Online learning for "thing-adaptive" Fog Computing in IoT. - Tianyi Chen; Yanning Shen; Qing Ling 001; Georgios B. Giannakis (ACSSC, 2017)

Directed network topology inference via sparse joint diagonalization. - Yanning Shen; Xiao Fu 001; Georgios B. Giannakis; Nicholas D. Sidiropoulos (ACSSC, 2017)

Nonlinear dimensionality reduction on graphs. - Yanning Shen; Panagiotis A. Traganitis; Georgios B. Giannakis (CAMSAP, 2017)

Network topology inference via elastic net structural equation models. - Panagiotis A. Traganitis; Yanning Shen; Georgios B. Giannakis (EUSIPCO, 2017)

Topology inference of directed graphs using nonlinear structural vector autoregressive models. - Yanning Shen; Brian Baingana; Georgios B. Giannakis (ICASSP, 2017)

Topology inference of multilayer networks. - Panagiotis A. Traganitis; Yanning Shen; Georgios B. Giannakis (INFOCOM Workshops, 2017)

Kernel-Based Structural Equation Models for Topology Identification of Directed Networks. - Yanning Shen; Brian Baingana; Georgios B. Giannakis (IEEE Trans. Signal Process., 2017)

Tensor Decompositions for Identifying Directed Graph Topologies and Tracking Dynamic Networks. - Yanning Shen; Brian Baingana; Georgios B. Giannakis (IEEE Trans. Signal Process., 2017)

Online Categorical Subspace Learning for Sketching Big Data with Misses. - Yanning Shen; Morteza Mardani; Georgios B. Giannakis (IEEE Trans. Signal Process., 2017)

Signal and Graph Perturbations via Total Least-Squares. - Elena Ceci; Yanning Shen; Georgios B. Giannakis; Sergio Barbarossa (ACSSC, 2018)

Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments. - Yanning Shen; Tianyi Chen; Georgios B. Giannakis (AISTATS, 2018)

Semi-Blind Inference of Topologies and Signals over Graphs. - Vassilis N. Ioannidis; Yanning Shen; Georgios B. Giannakis (DSW, 2018)

Online Identification of Directional Graph Topologies Capturing Dynamic and Nonlinear Dependencies. - Yanning Shen; Georgios B. Giannakis (DSW, 2018)

Online Multi-Kernel Learning with Orthogonal Random Features. - Yanning Shen; Tianyi Chen; Georgios B. Giannakis (ICASSP, 2018)

Kernel-Based Semi-Supervised Learning Over Multilayer Graphs. - Vassilis N. Ioannidis; Panagiotis A. Traganitis; Yanning Shen; Georgios B. Giannakis (SPAWC, 2018)

Online Learning Adaptive to Dynamic and Adversarial Environments. - Yanning Shen; Tianyi Chen; Georgios B. Giannakis (SPAWC, 2018)

Canonical Correlation Analysis with Common Graph Priors. - Jia Chen 002; Gang Wang 014; Yanning Shen; Georgios B. Giannakis (SSP, 2018)

Semi-Blind Inference of Topologies and Dynamical Processes over Graphs. - Vassilis N. Ioannidis; Yanning Shen; Georgios B. Giannakis (CoRR, 2018)

Heterogeneous Online Learning for "Thing-Adaptive" Fog Computing in IoT. - Tianyi Chen; Qing Ling 001; Yanning Shen; Georgios B. Giannakis (IEEE Internet Things J., 2018)

Topology Identification and Learning over Graphs: Accounting for Nonlinearities and Dynamics. - Georgios B. Giannakis; Yanning Shen; Georgios Vasileios Karanikolas (Proc. IEEE, 2018)

Canonical Correlation Analysis of Datasets With a Common Source Graph. - Jia Chen 002; Gang Wang 014; Yanning Shen; Georgios B. Giannakis (IEEE Trans. Signal Process., 2018)

Scalable and Adaptive KNN for Regression Over Graphs. - Seth Barrash; Yanning Shen; Georgios B. Giannakis (CAMSAP, 2019)

Scalable Learning with Privacy Over Graphs. - Yanning Shen; Geert Leus (DSW, 2019)

Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics. - Yanning Shen; Tianyi Chen; Georgios B. Giannakis (J. Mach. Learn. Res., 2019)

Semi-Blind Inference of Topologies and Dynamical Processes Over Dynamic Graphs. - Vassilis N. Ioannidis; Yanning Shen; Georgios B. Giannakis (IEEE Trans. Signal Process., 2019)

Nonlinear Structural Vector Autoregressive Models With Application to Directed Brain Networks. - Yanning Shen; Georgios B. Giannakis; Brian Baingana (IEEE Trans. Signal Process., 2019)

Online Graph-Adaptive Learning With Scalability and Privacy. - Yanning Shen; Geert Leus; Georgios B. Giannakis (IEEE Trans. Signal Process., 2019)

Graph-aided Online Learning with Expert Advice. - Pouya M. Ghari; Yanning Shen (ACSSC, 2020)

Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability. - Qin Lu 002; Georgios Vasileios Karanikolas; Yanning Shen; Georgios B. Giannakis (AISTATS, 2020)

Online Multi-Kernel Learning with Graph-Structured Feedback. - Pouya M. Ghari; Yanning Shen (ICML, 2020)

Differentially Private Nonlinear Canonical Correlation Analysis. - Yanning Shen (SAM, 2020)

Topology Identification of Directed Graphs via Joint Diagonalization of Correlation Matrices. - Yanning Shen; Xiao Fu 001; Georgios B. Giannakis; Nicholas D. Sidiropoulos (IEEE Trans. Signal Inf. Process. over Networks, 2020)

Graph-Based Learning Under Perturbations via Total Least-Squares. - Elena Ceci; Yanning Shen; Georgios B. Giannakis; Sergio Barbarossa (IEEE Trans. Signal Process., 2020)

Online Multi-Hop Information Based Kernel Learning Over Graphs. - Zixiao Zong; Yanning Shen (ICASSP, 2021)

Fairness-Aware Node Representation Learning. - Öykü Deniz Köse; Yanning Shen (CoRR, 2021)

Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network. - Maosen Li; Siheng Chen; Yanning Shen; Genjia Liu; Ivor W. Tsang; Ya Zhang 002 (CoRR, 2021)

Distributed and Quantized Online Multi-Kernel Learning. - Yanning Shen; Saeed Karimi-Bidhendi; Hamid Jafarkhani (IEEE Trans. Signal Process., 2021)

Fairness-aware Graph Attention Networks. - Öykü Deniz Köse; Yanning Shen (IEEECONF, 2022)

Fairness-aware User Classification in Power Grids. - Ruijie Du; Yanning Shen (EUSIPCO, 2022)

Graph-Assisted Communication-Efficient Ensemble Federated Learning. - Pouya M. Ghari; Yanning Shen (EUSIPCO, 2022)

Fairness-aware Adaptive Network Link Prediction. - Oyku Deniz Kose; Yanning Shen (EUSIPCO, 2022)

Online Learning with Probabilistic Feedback. - Pouya M. Ghari; Yanning Shen (ICASSP, 2022)

Fairness-Aware Selective Sampling on Attributed Graphs. - Oyku Deniz Kose; Yanning Shen (ICASSP, 2022)

Personalized Online Federated Learning with Multiple Kernels. - Pouya M. Ghari; Yanning Shen (NeurIPS, 2022)

Fair Node Representation Learning via Adaptive Data Augmentation. - Öykü Deniz Köse; Yanning Shen (CoRR, 2022)

FairNorm: Fair and Fast Graph Neural Network Training. - Öykü Deniz Köse; Yanning Shen (CoRR, 2022)

Explaining Dynamic Graph Neural Networks via Relevance Back-propagation. - Jiaxuan Xie; Yezi Liu; Yanning Shen (CoRR, 2022)

Adaptive Control of Unknown Time Varying Dynamical Systems with Regret Guarantees. - Deepan Muthirayan; Ruijie Du; Yanning Shen; Pramod P. Khargonekar (CoRR, 2022)

Fair Contrastive Learning on Graphs. - Oyku Deniz Kose; Yanning Shen (IEEE Trans. Signal Inf. Process. over Networks, 2022)

Fairness-Aware Graph Filter Design. - Öykü Deniz Köse; Yanning Shen; Gonzalo Mateos (ACSSC, 2023)

Change Point Detection Approach for Online Control of Unknown Time Varying Dynamical Systems. - Deepan Muthirayan; Ruijie Du; Yanning Shen; Pramod P. Khargonekar (CDC, 2023)

Model Extraction Attacks Against Reinforcement Learning Based Controllers. - Momina Sajid; Yanning Shen; Yasser Shoukry (CDC, 2023)

Fairness-Aware Dimensionality Reduction. - Öykü Deniz Köse; Yanning Shen (EUSIPCO, 2023)

Dynamic Fair Node Representation Learning. - Oyku Deniz Kose; Yanning Shen (ICASSP, 2023)

Fairness in Graph Machine Learning: Recent Advances and Future Prospectives. - Yushun Dong; Oyku Deniz Kose; Yanning Shen; Jundong Li (KDD, 2023)

Fairness-aware Optimal Graph Filter Design. - Oyku Deniz Kose; Yanning Shen; Gonzalo Mateos (CoRR, 2023)

Graph-Aided Online Multi-Kernel Learning. - Pouya M. Ghari; Yanning Shen (J. Mach. Learn. Res., 2023)

Fast&Fair: Training Acceleration and Bias Mitigation for GNNs. - Oyku Deniz Kose; Yanning Shen (Trans. Mach. Learn. Res., 2023)

Multiple Kernel Representation Learning on Networks. - Abdulkadir Çelikkanat; Yanning Shen; Fragkiskos D. Malliaros (IEEE Trans. Knowl. Data Eng., 2023)

FairViT: Fair Vision Transformer via Adaptive Masking. - Bowei Tian; Ruijie Du; Yanning Shen (ECCV (65), 2024)

TinyData: Joint Dataset Condensation with Dimensionality Reduction. - Yezi Liu; Yanning Shen (EUSIPCO, 2024)

Filtering as Rewiring for Bias Mitigation on Graphs. - Oyku Deniz Kose; Gonzalo Mateos; Yanning Shen (SAM, 2024)

FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning. - Lisha Chen; A. F. M. Saif; Yanning Shen; Tianyi Chen (NeurIPS, 2024)

Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning. - Pouya M. Ghari; Yanning Shen (NeurIPS, 2024)

Multi-model Ensemble Conformal Prediction in Dynamic Environments. - Erfan Hajihashemi; Yanning Shen (NeurIPS, 2024)

FairWire: Fair Graph Generation. - Oyku Deniz Kose; Yanning Shen (NeurIPS, 2024)

TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks. - Yezi Liu; Yanning Shen (CoRR, 2024)

Gradient Inversion Attack on Graph Neural Networks. - Divya Anand Sinha; Yezi Liu; Ruijie Du; Yanning Shen (CoRR, 2024)

Budgeted Online Model Selection and Fine-Tuning via Federated Learning. - Pouya M. Ghari; Yanning Shen (Trans. Mach. Learn. Res., 2024)

Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks. - Maosen Li; Siheng Chen; Yanning Shen; Genjia Liu; Ivor W. Tsang; Ya Zhang 002 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Online Learning With Uncertain Feedback Graphs. - Pouya M. Ghari; Yanning Shen (IEEE Trans. Neural Networks Learn. Syst., 2024)

FairGAT: Fairness-Aware Graph Attention Networks. - Öykü Deniz Köse; Yanning Shen (ACM Trans. Knowl. Discov. Data, 2024)

Demystifying and Mitigating Bias for Node Representation Learning. - Oyku Deniz Kose; Yanning Shen (IEEE Trans. Neural Networks Learn. Syst., 2024)

FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge. - Tianyu Zhang; Shen Dong; Oyku Deniz Kose; Yanning Shen; Yupeng Zhang (SP, 2025)

Beyond Node Condensation: Learning Tiny Graphs via Joint Graph Condensation. - Yezi Liu; Yanning Shen (WWW (Companion Volume), 2025)

Gradient Inversion Attack on Graph Neural Networks. - Divya Anand Sinha; Yezi Liu; Ruijie Du; Athina Markopoulou; Yanning Shen (Trans. Mach. Learn. Res., 2025)

CAD-VAE: Leveraging Correlation-Aware Latents for Comprehensive Fair Disentanglement. - Chenrui Ma; Rongchang Zhao; Xi Xiao; Hongyang Xie; Tianyang Wang; Xiao Wang 004; Hao Zhang; Yanning Shen (CoRR, 2025)

FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge. - Tianyu Zhang; Shen Dong; O. Deniz Kose; Yanning Shen; Yupeng Zhang (CoRR, 2025)

Unlearning Algorithmic Biases over Graphs. - Öykü Deniz Köse; Gonzalo Mateos; Yanning Shen (CoRR, 2025)

Beyond Editing Pairs: Fine-Grained Instructional Image Editing via Multi-Scale Learnable Regions. - Chenrui Ma; Xi Xiao; Tianyang Wang; Yanning Shen (CoRR, 2025)

Is Noise Conditioning Necessary? A Unified Theory of Unconditional Graph Diffusion Models. - Jipeng Li; Yanning Shen (CoRR, 2025)

Graph-Structured Feedback Multimodel Ensemble Online Conformal Prediction. - Erfan Hajihashemi; Yanning Shen (CoRR, 2025)

Long-Term Fairness for Real-Time Decision Making: A Constrained Online Optimization Approach. - Ruijie Du; Deepan Muthirayan; Pramod P. Khargonekar; Yanning Shen (IEEE Trans. Neural Networks Learn. Syst., 2025)

Learn to Explore: Meta NAS via Bayesian Optimization Guided Graph Generation. - Zijun Sun; Yanning Shen (CoRR, 2025)

EGGS-PTP: An Expander-Graph Guided Structured Post-training Pruning Method for Large Language Models. - Omar Bazarbachi; Zijun Sun; Yanning Shen (CoRR, 2025)