Xiao Fu

Orcid: 0000-0003-4847-9586

Affiliations:
  • Oregon State University, School of Electrical Engineering and Computer Science, Corvallis, OR, USA
  • University of Minnesota, Department of Electrical and Computer Engineering, Minneapolis, MN, USA
  • The Chinese University of Hong Kong, Electronic Engineering, Shatin, Hong Kong (PhD 2014)


According to our database1, Xiao Fu authored at least 144 papers between 2009 and 2024.

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

Timeline

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Bibliography

2024
Snapshot Compressive Imaging Using Domain-Factorized Deep Video Prior.
IEEE Trans. Computational Imaging, 2024

Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures.
CoRR, 2024

Hyperspectral Unmixing Under Endmember Variability: A Variational Inference Framework.
CoRR, 2024

Learning From Crowdsourced Noisy Labels: A Signal Processing Perspective.
CoRR, 2024

Translation Identifiability-Guided Unsupervised Cross-Platform Super-Resolution for OCT Images.
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Labeling Sequential Data From Noisy Annotations.
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Smoothed Bregman Proximal Gradient Algorithm for Decentralized Nonconvex Optimization.
Proceedings of the IEEE International Conference on Acoustics, 2024

Probabilistic Simplex Component Analysis via Variational Auto-Encoding.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Finite-Sample Analysis of Deep CCA-Based Unsupervised Post-Nonlinear Multimodal Learning.
IEEE Trans. Neural Networks Learn. Syst., November, 2023

On Local Linear Convergence of Projected Gradient Descent for Unit-Modulus Least Squares.
IEEE Trans. Signal Process., 2023

Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Graph Neural Imitation Learning.
IEEE Trans. Signal Process., 2023

Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis.
IEEE Trans. Signal Process., 2023

Fast and Structured Block-Term Tensor Decomposition for Hyperspectral Unmixing.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Quantized Radio Map Estimation Using Tensor and Deep Generative Models.
CoRR, 2023

Transformer Based Approach for Wireless Resource Allocation Problems Involving Mixed Discrete and Continuous Variables.
Proceedings of the 24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2023

Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach.
Proceedings of the International Conference on Machine Learning, 2023

Under-Counted Tensor Completion with Neural Incorporation of Attributes.
Proceedings of the International Conference on Machine Learning, 2023

Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Deep Spectrum Cartography Using Quantized Measurements.
Proceedings of the IEEE International Conference on Acoustics, 2023

Towards Efficient and Optimal Joint Beamforming and Antenna Selection: A Machine Learning Approach.
Proceedings of the IEEE International Conference on Acoustics, 2023

Bilinear Hyperspectral Unmixing via Tensor Decomposition.
Proceedings of the 31st European Signal Processing Conference, 2023

Deep Learning from Noisy Labels via Robust Nonnegative Matrix Factorization-Based Design.
Proceedings of the 9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2023

2022
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective.
IEEE Trans. Signal Process., 2022

Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models.
IEEE Trans. Signal Process., 2022

Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses.
IEEE Trans. Signal Process., 2022

Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach.
IEEE Trans. Signal Process., 2022

Hyperspectral Denoising Using Unsupervised Disentangled Spatiospectral Deep Priors.
IEEE Trans. Geosci. Remote. Sens., 2022

Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Machine Learning.
CoRR, 2022

Provable Subspace Identification Under Post-Nonlinear Mixtures.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis.
Proceedings of the International Conference on Machine Learning, 2022

Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Communication-Efficient Distributed MAX-VAR Generalized CCA via Error Feedback-Assisted Quantization.
Proceedings of the IEEE International Conference on Acoustics, 2022

Massive MIMO Channel Estimation via Compressed and Quantized Feedback.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

Memory-Efficient Convex Optimization for Self-Dictionary Nonnegative Matrix Factorization.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder.
IEEE Trans. Signal Process., 2021

Mixed Membership Graph Clustering via Systematic Edge Query.
IEEE Trans. Signal Process., 2021

Recovering Joint Probability of Discrete Random Variables From Pairwise Marginals.
IEEE Trans. Signal Process., 2021

Link Prediction Under Imperfect Detection: Collaborative Filtering for Ecological Networks.
IEEE Trans. Knowl. Data Eng., 2021

Multi-User Adaptive Video Delivery Over Wireless Networks: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach.
IEEE Trans. Circuits Syst. Video Technol., 2021

Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modeling.
IEEE J. Sel. Top. Signal Process., 2021

Uncovering migration systems through spatio-temporal tensor co-clustering.
CoRR, 2021

Communication-Efficient Distributed Linear and Deep Generalized Canonical Correlation Analysis.
CoRR, 2021

Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective.
CoRR, 2021

Hyperspectral Denoising Using Unsupervised Disentangled Spatio-Spectral Deep Priors.
CoRR, 2021

Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning to Continuously Optimize Wireless Resource in Episodically Dynamic Environment.
Proceedings of the IEEE International Conference on Acoustics, 2021

Deep Generative Model Learning For Blind Spectrum Cartography with NMF-Based Radio Map Disaggregation.
Proceedings of the IEEE International Conference on Acoustics, 2021

Fiber-Sampled Stochastic Mirror Descent for Tensor Decomposition with β-Divergence.
Proceedings of the IEEE International Conference on Acoustics, 2021

Learning Mixed Membership from Adjacency Graph Via Systematic Edge Query: Identifiability and Algorithm.
Proceedings of the IEEE International Conference on Acoustics, 2021

Constrained Block-Term Tensor Decomposition-Based Hyperspectral Unmixing via Alternating Gradient Projection.
Proceedings of the 29th European Signal Processing Conference, 2021

VLSI Hardware Architecture of Stochastic Low-rank Tensor Decomposition.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Spectrum Cartography via Coupled Block-Term Tensor Decomposition.
IEEE Trans. Signal Process., 2020

Learning Nonlinear Mixtures: Identifiability and Algorithm.
IEEE Trans. Signal Process., 2020

Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization - Part II: Applications.
IEEE Trans. Signal Process., 2020

Nonlinear Multiview Analysis: Identifiability and Neural Network-Assisted Implementation.
IEEE Trans. Signal Process., 2020

Tensor Completion From Regular Sub-Nyquist Samples.
IEEE Trans. Signal Process., 2020

Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization.
IEEE Trans. Signal Process., 2020

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

Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation.
IEEE Trans. Geosci. Remote. Sens., 2020

Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective.
IEEE Signal Process. Mag., 2020

On Recoverability of Randomly Compressed Tensors With Low CP Rank.
IEEE Signal Process. Lett., 2020

Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors.
CoRR, 2020

Nonlinear Multiview Analysis: Identifiability and Neural Network-based Implementation.
Proceedings of the 11th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020

Low-Complexity Levenberg-Marquardt Algorithm for Tensor Canonical Polyadic Decomposition.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Nonlinear Dependent Component Analysis: Identifiability and Algorithm.
Proceedings of the 28th European Signal Processing Conference, 2020

Recovering Joint PMF from Pairwise Marginals.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data.
IEEE Trans. Signal Process., 2019

Efficient and Distributed Generalized Canonical Correlation Analysis for Big Multiview Data.
IEEE Trans. Knowl. Data Eng., 2019

Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications.
IEEE Signal Process. Mag., 2019

Amplitude Retrieval for Channel Estimation of MIMO Systems With One-Bit ADCs.
IEEE Signal Process. Lett., 2019

Anchor-Free Correlated Topic Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Algebraic Channel Estimation Algorithms for FDD Massive MIMO Systems.
IEEE J. Sel. Top. Signal Process., 2019

Neural Network-Assisted Nonlinear Multiview Component Analysis: Identifiability and Algorithm.
CoRR, 2019

Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization.
CoRR, 2019

Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach.
Proceedings of the 2019 IEEE Visual Communications and Image Processing, 2019

A Simple Algebraic Channel Estimation Method for FDD Massive MIMO Systems.
Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

ON Convergence of Projected Gradient Descent for Minimizing a Large-Scale Quadratic Over the Unit Sphere.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Block-Term Tensor Decomposition Via Constrained Matrix Factorization.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm.
Proceedings of the 36th International Conference on Machine Learning, 2019

Regular Sampling of Tensor Signals: Theory and Application to FMRI.
Proceedings of the IEEE International Conference on Acoustics, 2019

Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization.
Proceedings of the IEEE International Conference on Acoustics, 2019

Low-complexity Proximal Gauss-Newton Algorithm for Nonnegative Matrix Factorization.
Proceedings of the 2019 IEEE Global Conference on Signal and Information Processing, 2019

Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical Learning.
Proceedings of the IEEE Data Science Workshop, 2019

Hyperspectral Super-Resolution: A Coupled Nonnegative Block-Term Tensor Decomposition Approach.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Coupled Block-term Tensor Decomposition Based Blind Spectrum Cartography.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Unsupervised Learning of Nonlinear Mixtures: Identifiability and Algorithm.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Learning to Optimize: Training Deep Neural Networks for Interference Management.
IEEE Trans. Signal Process., 2018

MISO Channel Estimation and Tracking from Received Signal Strength Feedback.
IEEE Trans. Signal Process., 2018

Tensor-Based Channel Estimation for Dual-Polarized Massive MIMO Systems.
IEEE Trans. Signal Process., 2018

Tensors, Learning, and "Kolmogorov Extension" for Finite-Alphabet Random Vectors.
IEEE Trans. Signal Process., 2018

Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach.
IEEE Trans. Signal Process., 2018

Limited Feedback Channel Estimation in Massive MIMO With Non-Uniform Directional Dictionaries.
IEEE Trans. Signal Process., 2018

On Identifiability of Nonnegative Matrix Factorization.
IEEE Signal Process. Lett., 2018

Learning Hidden Markov Models from Pairwise Co-occurrences with Applications to Topic Modeling.
CoRR, 2018

A Convex Low-Rank Regularization Method for Hyperspectral Super-Resolution.
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Limited Feedback Double Directional Massive MIMO Channel Estimation: From Low-Rank Modeling to Deep Learning.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Learning-Based Antenna Selection for Multicasting.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling.
Proceedings of the 35th International Conference on Machine Learning, 2018

Hyperspectral Super-Resolution: Combining Low Rank Tensor and Matrix Structure.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Hi, Bcd! Hybrid Inexact Block Coordinate Descent for Hyperspectral Super-Resolution.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Hyperspectral Super-Resolution Via Coupled Tensor Factorization: Identifiability and Algorithms.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Large-Scale Regularized Sumcor GCCA via Penalty-Dual Decomposition.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Tensor-Based Parameter Estimation of Double Directional Massive Mimo Channel with Dual-Polarized Antennas.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

On Convergence of Epanechnikov Mean Shift.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering.
IEEE Trans. Signal Process., 2017

Fast Unit-Modulus Least Squares With Applications in Beamforming.
IEEE Trans. Signal Process., 2017

Tensor Decomposition for Signal Processing and Machine Learning.
IEEE Trans. Signal Process., 2017

Inexact Alternating Optimization for Phase Retrieval in the Presence of Outliers.
IEEE Trans. Signal Process., 2017

Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis.
IEEE Trans. Signal Process., 2017

Penalty Dual Decomposition Method For Nonsmooth Nonconvex Optimization.
CoRR, 2017

Non-uniform directional dictionary-based limited feedback for massive MIMO systems.
Proceedings of the 15th International Symposium on Modeling and Optimization in Mobile, 2017

Learning to optimize: Training deep neural networks for wireless resource management.
Proceedings of the 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2017

BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering.
Proceedings of the 34th International Conference on Machine Learning, 2017

A stochastic maximum-likelihood framework for simplex structured matrix factorization.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Scalable and flexible Max-Var generalized canonical correlation analysis via alternating optimization.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Distributed optimal power flow using feasible point pursuit.
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

2016
Power Spectra Separation via Structured Matrix Factorization.
IEEE Trans. Signal Process., 2016

Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering.
IEEE Trans. Signal Process., 2016

Semiblind Hyperspectral Unmixing in the Presence of Spectral Library Mismatches.
IEEE Trans. Geosci. Remote. Sens., 2016

Robustness Analysis of Structured Matrix Factorization via Self-Dictionary Mixed-Norm Optimization.
IEEE Signal Process. Lett., 2016

Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Efficient and Distributed Algorithms for Large-Scale Generalized Canonical Correlations Analysis.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Robust volume minimization-based matrix factorization via alternating optimization.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Fast unit-modulus least squares with applications in transmit beamforming.
Proceedings of the 24th European Signal Processing Conference, 2016

Inexact alternating optimization for phase retrieval with outliers.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
A Factor Analysis Framework for Power Spectra Separation and Multiple Emitter Localization.
IEEE Trans. Signal Process., 2015

Blind Separation of Quasi-Stationary Sources: Exploiting Convex Geometry in Covariance Domain.
IEEE Trans. Signal Process., 2015

Joint Tensor Factorization and Outlying Slab Suppression With Applications.
IEEE Trans. Signal Process., 2015

Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search Are Related.
IEEE J. Sel. Top. Signal Process., 2015

Translation Invariant Word Embeddings.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Joint factor analysis and latent clustering.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
A robust subspace method for semiblind dictionary-aided hyperspectral unmixing.
Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014

Tensor-based power spectra separation and emitter localization for cognitive radio.
Proceedings of the IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, 2014

Blind spectra separation and direction finding for cognitive radio using temporal correlation-domain ESPRIT.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
A Khatri-Rao subspace approach to blind identification of mixtures of quasi-stationary sources.
Signal Process., 2013

Blind separation of convolutive mixtures of speech sources: Exploiting local sparsity.
Proceedings of the IEEE International Conference on Acoustics, 2013

Greedy algorithms for pure pixels identification in hyperspectral unmixing: A multiple-measurement vector viewpoint.
Proceedings of the 21st European Signal Processing Conference, 2013

2012
A simple closed-form solution for overdetermined blind separation of locally sparse quasi-stationary sources.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2009
Joint power management and beamforming for base stations in Cognitive Radio systems.
Proceedings of the 2009 6th International Symposium on Wireless Communication Systems, 2009


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