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ORCIDXiao Fu 0001
Person information
- affiliation: Oregon State University, School of Electrical Engineering and Computer Science, Corvallis, OR, USA
- affiliation: University of Minnesota, Department of Electrical and Computer Engineering, Minneapolis, MN, USA
- affiliation (PhD 2014): The Chinese University of Hong Kong, Electronic Engineering, Shatin, Hong Kong
Other persons with the same name
- Fu Xiao (aka: Xiao Fu) — disambiguation page
- Xiao Fu 0002
![[0000-0003-0221-0063]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0221-0063")
— Beijing University of Posts and Telecommunications, School of Electronic Engineering, China - Xiao Fu 0003 — University of Manchester, UK
- Xiao Fu 0004 (aka: Fu Xiao 0004) — Tianjin University, State Key Lab of Precision Measuring Technology and Instruments, China
- Xiao Fu 0005 — Nanjing University, State Key Laboratory for Novel Software Technology, China
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2020 – today
- 2024
[j54]Yu-Chun Miao, Xi-Le Zhao, Jian-Li Wang, Xiao Fu, Yao Wang:
Snapshot Compressive Imaging Using Domain-Factorized Deep Video Prior. IEEE Trans. Computational Imaging 10: 93-102 (2024)- [i46]Sagar Shrestha, Xiao Fu:
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach. CoRR abs/2401.09671 (2024) - 2023
- [j53]Meng Ding, Xiao Fu, Xi-Le Zhao:
Fast and Structured Block-Term Tensor Decomposition for Hyperspectral Unmixing. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16: 1691-1709 (2023) - [j52]Qi Lyu, Xiao Fu:
Finite-Sample Analysis of Deep CCA-Based Unsupervised Post-Nonlinear Multimodal Learning. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9568-9574 (2023) - [j51]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Graph Neural Imitation Learning. IEEE Trans. Signal Process. 71: 831-846 (2023) - [j50]Sagar Shrestha, Xiao Fu:
Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis. IEEE Trans. Signal Process. 71: 1379-1394 (2023) - [j49]Trung Vu, Raviv Raich, Xiao Fu:
On Local Linear Convergence of Projected Gradient Descent for Unit-Modulus Least Squares. IEEE Trans. Signal Process. 71: 3883-3897 (2023) - [c69]Daniel Grey Wolnick, Shahana Ibrahim, Tim Marrinan, Xiao Fu:
Deep Learning from Noisy Labels via Robust Nonnegative Matrix Factorization-Based Design. CAMSAP 2023: 446-450 - [c68]Meng Ding, Xiao Fu, Xi-Le Zhao:
Bilinear Hyperspectral Unmixing via Tensor Decomposition. EUSIPCO 2023: 640-644 - [c67]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Towards Efficient and Optimal Joint Beamforming and Antenna Selection: A Machine Learning Approach. ICASSP 2023: 1-5 - [c66]Subash Timilsina, Sagar Shrestha, Xiao Fu:
Deep Spectrum Cartography Using Quantized Measurements. ICASSP 2023: 1-5 - [c65]Shahana Ibrahim, Tri Nguyen, Xiao Fu:
Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization. ICLR 2023 - [c64]Shahana Ibrahim, Xiao Fu, Rebecca A. Hutchinson, Eugene Seo:
Under-Counted Tensor Completion with Neural Incorporation of Attributes. ICML 2023: 14283-14315 - [c63]Tri Nguyen, Shahana Ibrahim, Xiao Fu:
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach. ICML 2023: 25980-26007 - [c62]Bingqing Song, Zhicheng Zhou, Chenliang Li, Dongning Guo, Xiao Fu, Mingyi Hong:
Transformer Based Approach for Wireless Resource Allocation Problems Involving Mixed Discrete and Continuous Variables. SPAWC 2023: 636-640 - [i45]Subash Timilsina, Sagar Shrestha, Xiao Fu:
Quantized Radio Map Estimation Using Tensor and Deep Generative Models. CoRR abs/2303.01770 (2023) - [i44]Tri Nguyen, Shahana Ibrahim, Xiao Fu:
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach. CoRR abs/2305.19391 (2023) - [i43]Shahana Ibrahim, Xiao Fu, Rebecca A. Hutchinson, Eugene Seo:
Under-Counted Tensor Completion with Neural Incorporation of Attributes. CoRR abs/2306.03273 (2023) - [i42]Shahana Ibrahim, Tri Nguyen, Xiao Fu:
Deep Learning From Crowdsourced Labels: Coupled Cross-entropy Minimization, Identifiability, and Regularization. CoRR abs/2306.03288 (2023) - 2022
- [j48]Yu-Chun Miao, Xi-Le Zhao, Xiao Fu, Jian-Li Wang, Yu-Bang Zheng:
Hyperspectral Denoising Using Unsupervised Disentangled Spatiospectral Deep Priors. IEEE Trans. Geosci. Remote. Sens. 60: 1-16 (2022) - [j47]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models. IEEE Trans. Signal Process. 70: 1170-1184 (2022) - [j46]Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong:
Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses. IEEE Trans. Signal Process. 70: 1803-1818 (2022) - [j45]Haoran Sun, Wenqiang Pu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong:
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective. IEEE Trans. Signal Process. 70: 1900-1917 (2022) - [j44]Tri Nguyen, Xiao Fu, Ruiyuan Wu:
Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach. IEEE Trans. Signal Process. 70: 3221-3236 (2022) - [c61]Mingjie Shao, Xiao Fu:
Massive MIMO Channel Estimation via Compressed and Quantized Feedback. IEEECONF 2022: 1016-1020 - [c60]Tri Nguyen, Xiao Fu, Ruiyuan Wu:
Memory-Efficient Convex Optimization for Self-Dictionary Nonnegative Matrix Factorization. IEEECONF 2022: 1372-1376 - [c59]Sagar Shrestha, Xiao Fu:
Communication-Efficient Distributed MAX-VAR Generalized CCA via Error Feedback-Assisted Quantization. ICASSP 2022: 9052-9056 - [c58]Qi Lyu, Xiao Fu, Weiran Wang, Songtao Lu:
Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective. ICLR 2022 - [c57]Qi Lyu, Xiao Fu:
On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis. ICML 2022: 14582-14600 - [c56]Qi Lyu, Xiao Fu:
Provable Subspace Identification Under Post-Nonlinear Mixtures. NeurIPS 2022 - [i41]Meng Ding, Xiao Fu, Xi-Le Zhao:
Fast and Structured Block-Term Tensor Decomposition For Hyperspectral Unmixing. CoRR abs/2205.03798 (2022) - [i40]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Machine Learning. CoRR abs/2206.05576 (2022) - [i39]Qi Lyu, Xiao Fu:
On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis. CoRR abs/2206.06593 (2022) - [i38]Qi Lyu, Xiao Fu:
Provable Subspace Identification Under Post-Nonlinear Mixtures. CoRR abs/2210.07532 (2022) - 2021
- [j43]Meng Ding, Xiao Fu, Ting-Zhu Huang, Jun Wang, Xi-Le Zhao:
Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modeling. IEEE J. Sel. Top. Signal Process. 15(3): 641-656 (2021) - [j42]Kexin Tang, Nuowen Kan, Junni Zou, Chenglin Li, Xiao Fu, Mingyi Hong, Hongkai Xiong:
Multi-User Adaptive Video Delivery Over Wireless Networks: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach. IEEE Trans. Circuits Syst. Video Technol. 31(2): 798-815 (2021) - [j41]Xiao Fu, Eugene Seo, Justin Clarke, Rebecca A. Hutchinson:
Link Prediction Under Imperfect Detection: Collaborative Filtering for Ecological Networks. IEEE Trans. Knowl. Data Eng. 33(8): 3117-3128 (2021) - [j40]Shahana Ibrahim, Xiao Fu:
Recovering Joint Probability of Discrete Random Variables From Pairwise Marginals. IEEE Trans. Signal Process. 69: 4116-4131 (2021) - [j39]Qi Lyu, Xiao Fu:
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder. IEEE Trans. Signal Process. 69: 4921-4936 (2021) - [j38]Shahana Ibrahim, Xiao Fu:
Mixed Membership Graph Clustering via Systematic Edge Query. IEEE Trans. Signal Process. 69: 5189-5205 (2021) - [c55]Eugene Seo, Rebecca A. Hutchinson, Xiao Fu, Chelsea Li, Tyler A. Hallman, John Kilbride, W. Douglas Robinson:
StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling. AAAI 2021: 513-521 - [c54]Lingyi Huang, Chunhua Deng, Shahana Ibrahim, Xiao Fu, Bo Yuan:
VLSI Hardware Architecture of Stochastic Low-rank Tensor Decomposition. ACSCC 2021: 1176-1180 - [c53]Meng Ding, Xiao Fu, Ting-Zhu Huang, Xi-Le Zhao:
Constrained Block-Term Tensor Decomposition-Based Hyperspectral Unmixing via Alternating Gradient Projection. EUSIPCO 2021: 1060-1064 - [c52]Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong:
Fiber-Sampled Stochastic Mirror Descent for Tensor Decomposition with β-Divergence. ICASSP 2021: 2925-2929 - [c51]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Deep Generative Model Learning For Blind Spectrum Cartography with NMF-Based Radio Map Disaggregation. ICASSP 2021: 4920-4924 - [c50]Haoran Sun, Wenqiang Pu, Minghe Zhu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong:
Learning to Continuously Optimize Wireless Resource in Episodically Dynamic Environment. ICASSP 2021: 4945-4949 - [c49]Shahana Ibrahim, Xiao Fu:
Learning Mixed Membership from Adjacency Graph Via Systematic Edge Query: Identifiability and Algorithm. ICASSP 2021: 5370-5374 - [c48]Shahana Ibrahim, Xiao Fu:
Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization. ICML 2021: 4544-4554 - [i37]Eugene Seo, Rebecca A. Hutchinson, Xiao Fu, Chelsea Li, Tyler A. Hallman, John Kilbride, W. Douglas Robinson:
StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling. CoRR abs/2102.08534 (2021) - [i36]Yu-Chun Miao, Xi-Le Zhao, Xiao Fu, Jian-Li Wang, Yu-Bang Zheng:
Hyperspectral Denoising Using Unsupervised Disentangled Spatio-Spectral Deep Priors. CoRR abs/2102.12310 (2021) - [i35]Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong:
Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses. CoRR abs/2104.14562 (2021) - [i34]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models. CoRR abs/2105.00177 (2021) - [i33]Haoran Sun, Wenqiang Pu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong:
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective. CoRR abs/2105.01696 (2021) - [i32]Qi Lyu, Xiao Fu, Weiran Wang, Songtao Lu:
Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective. CoRR abs/2106.07115 (2021) - [i31]Shahana Ibrahim, Xiao Fu:
Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization. CoRR abs/2106.07193 (2021) - [i30]Qi Lyu, Xiao Fu:
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder. CoRR abs/2106.09070 (2021) - [i29]Tri Nguyen, Xiao Fu, Ruiyuan Wu:
Memory-Efficient Convex Optimization for Self-Dictionary Separable Nonnegative Matrix Factorization: A Frank-Wolfe Approach. CoRR abs/2109.11135 (2021) - [i28]Sagar Shrestha, Xiao Fu:
Communication-Efficient Distributed Linear and Deep Generalized Canonical Correlation Analysis. CoRR abs/2109.12400 (2021) - [i27]Zack W. Almquist, Tri Duc Nguyen, Mikael Sørensen, Xiao Fu, Nicholas D. Sidiropoulos:
Uncovering migration systems through spatio-temporal tensor co-clustering. CoRR abs/2112.15296 (2021) - 2020
- [j37]Shahana Ibrahim, Xiao Fu, Xingguo Li:
On Recoverability of Randomly Compressed Tensors With Low CP Rank. IEEE Signal Process. Lett. 27: 1125-1129 (2020) - [j36]Xiao Fu, Nico Vervliet, Lieven De Lathauwer, Kejun Huang, Nicolas Gillis:
Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective. IEEE Signal Process. Mag. 37(5): 78-94 (2020) - [j35]Ruiyuan Wu, Wing-Kin Ma, Xiao Fu, Qiang Li:
Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation. IEEE Trans. Geosci. Remote. Sens. 58(10): 7125-7140 (2020) - [j34]Yanning Shen, Xiao Fu, Georgios B. Giannakis, Nicholas D. Sidiropoulos:
Topology Identification of Directed Graphs via Joint Diagonalization of Correlation Matrices. IEEE Trans. Signal Inf. Process. over Networks 6: 271-283 (2020) - [j33]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mehmet Akçakaya:
Tensor Completion From Regular Sub-Nyquist Samples. IEEE Trans. Signal Process. 68: 1-16 (2020) - [j32]Xiao Fu, Shahana Ibrahim, Hoi-To Wai, Cheng Gao, Kejun Huang:
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. IEEE Trans. Signal Process. 68: 2170-2185 (2020) - [j31]Qi Lyu, Xiao Fu:
Nonlinear Multiview Analysis: Identifiability and Neural Network-Assisted Implementation. IEEE Trans. Signal Process. 68: 2697-2712 (2020) - [j30]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Kejun Huang:
Learning Nonlinear Mixtures: Identifiability and Algorithm. IEEE Trans. Signal Process. 68: 2857-2869 (2020) - [j29]Guoyong Zhang, Xiao Fu, Jun Wang, Xi-Le Zhao, Mingyi Hong:
Spectrum Cartography via Coupled Block-Term Tensor Decomposition. IEEE Trans. Signal Process. 68: 3660-3675 (2020) - [j28]Qingjiang Shi, Mingyi Hong, Xiao Fu, Tsung-Hui Chang:
Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization - Part II: Applications. IEEE Trans. Signal Process. 68: 4242-4257 (2020) - [c47]Shahana Ibrahim, Xiao Fu:
Recovering Joint PMF from Pairwise Marginals. ACSSC 2020: 356-360 - [c46]Qi Lyu, Xiao Fu:
Nonlinear Dependent Component Analysis: Identifiability and Algorithm. EUSIPCO 2020: 1010-1014 - [c45]Kejun Huang, Xiao Fu:
Low-Complexity Levenberg-Marquardt Algorithm for Tensor Canonical Polyadic Decomposition. ICASSP 2020: 3922-3926 - [c44]Qi Lyu, Xiao Fu:
Nonlinear Multiview Analysis: Identifiability and Neural Network-based Implementation. SAM 2020: 1-5 - [i26]Xiao Fu, Nico Vervliet, Lieven De Lathauwer, Kejun Huang, Nicolas Gillis:
Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors. CoRR abs/2006.08183 (2020) - [i25]Shahana Ibrahim, Xiao Fu:
Recovering Joint Probability of Discrete Random Variables from Pairwise Marginals. CoRR abs/2006.16912 (2020) - [i24]Haoran Sun, Wenqiang Pu, Minghe Zhu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong:
Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment. CoRR abs/2011.07782 (2020) - [i23]Shahana Ibrahim, Xiao Fu:
Mixed Membership Graph Clustering via Systematic Edge Query. CoRR abs/2011.12988 (2020)
2010 – 2019
- 2019
- [j27]Cheng Qian, Xiao Fu, Nikolaos D. Sidiropoulos:
Algebraic Channel Estimation Algorithms for FDD Massive MIMO Systems. IEEE J. Sel. Top. Signal Process. 13(5): 961-973 (2019) - [j26]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos, Qingjiang Shi, Mingyi Hong:
Anchor-Free Correlated Topic Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1056-1071 (2019) - [j25]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos:
Amplitude Retrieval for Channel Estimation of MIMO Systems With One-Bit ADCs. IEEE Signal Process. Lett. 26(11): 1698-1702 (2019) - [j24]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications. IEEE Signal Process. Mag. 36(2): 59-80 (2019) - [j23]Xiao Fu, Kejun Huang, Evangelos E. Papalexakis, Hyun Ah Song, Partha P. Talukdar, Nicholas D. Sidiropoulos, Christos Faloutsos, Tom M. Mitchell:
Efficient and Distributed Generalized Canonical Correlation Analysis for Big Multiview Data. IEEE Trans. Knowl. Data Eng. 31(12): 2304-2318 (2019) - [j22]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. IEEE Trans. Signal Process. 67(2): 306-319 (2019) - [c43]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Kejun Huang:
Unsupervised Learning of Nonlinear Mixtures: Identifiability and Algorithm. ACSSC 2019: 1040-1044 - [c42]Guoyong Zhang, Xiao Fu, Jun Wang, Mingyi Hong:
Coupled Block-term Tensor Decomposition Based Blind Spectrum Cartography. ACSSC 2019: 1644-1648 - [c41]Guoyong Zhang, Xiao Fu, Kejun Huang, Jun Wang:
Hyperspectral Super-Resolution: A Coupled Nonnegative Block-Term Tensor Decomposition Approach. CAMSAP 2019: 470-474 - [c40]Shahana Ibrahim, Xiao Fu:
Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical Learning. DSW 2019: 300-304 - [c39]Kejun Huang, Xiao Fu:
Low-complexity Proximal Gauss-Newton Algorithm for Nonnegative Matrix Factorization. GlobalSIP 2019: 1-5 - [c38]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos, Mehmet Akçakaya, Xiao Fu:
Regular Sampling of Tensor Signals: Theory and Application to FMRI. ICASSP 2019: 2932-2936 - [c37]Xiao Fu, Cheng Gao, Hoi-To Wai, Kejun Huang:
Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization. ICASSP 2019: 7485-7489 - [c36]Kejun Huang, Xiao Fu:
Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm. ICML 2019: 2859-2868 - [c35]Xiao Fu, Kejun Huang:
Block-Term Tensor Decomposition Via Constrained Matrix Factorization. MLSP 2019: 1-6 - [c34]Shahana Ibrahim, Xiao Fu, Nikolaos Kargas, Kejun Huang:
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms. NeurIPS 2019: 7845-7855 - [c33]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos:
A Simple Algebraic Channel Estimation Method for FDD Massive MIMO Systems. SPAWC 2019: 1-5 - [c32]Kexin Tang, Nuowen Kan, Junni Zou, Xiao Fu, Mingyi Hong, Hongkai Xiong:
Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach. VCIP 2019: 1-4 - [i22]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Kejun Huang:
Learning Nonlinear Mixtures: Identifiability and Algorithm. CoRR abs/1901.01568 (2019) - [i21]Xiao Fu, Cheng Gao, Hoi-To Wai, Kejun Huang:
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. CoRR abs/1901.05529 (2019) - [i20]Kexin Tang, Nuowen Kan, Junni Zou, Xiao Fu, Mingyi Hong, Hongkai Xiong:
Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach. CoRR abs/1902.00637 (2019) - [i19]Ruiyuan Wu, Wing-Kin Ma, Xiao Fu, Qiang Li:
Hyperspectral Super-Resolution via Global-Local Low-Rank Matrix Estimation. CoRR abs/1907.01149 (2019) - [i18]Qi Lyu, Xiao Fu:
Neural Network-Assisted Nonlinear Multiview Component Analysis: Identifiability and Algorithm. CoRR abs/1909.09177 (2019) - [i17]Shahana Ibrahim, Xiao Fu, Nikos Kargas, Kejun Huang:
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms. CoRR abs/1909.12325 (2019) - [i16]Xiao Fu, Eugene Seo, Justin Clarke, Rebecca A. Hutchinson:
Link Prediction Under Imperfect Detection: Collaborative Filtering for Ecological Networks. CoRR abs/1910.03659 (2019) - 2018
- [j21]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos:
On Identifiability of Nonnegative Matrix Factorization. IEEE Signal Process. Lett. 25(3): 328-332 (2018) - [j20]Tianyu Qiu, Xiao Fu, Nicholas D. Sidiropoulos, Daniel P. Palomar:
MISO Channel Estimation and Tracking from Received Signal Strength Feedback. IEEE Trans. Signal Process. 66(7): 1691-1704 (2018) - [j19]Nikos Kargas, Nicholas D. Sidiropoulos, Xiao Fu:
Tensors, Learning, and "Kolmogorov Extension" for Finite-Alphabet Random Vectors. IEEE Trans. Signal Process. 66(18): 4854-4868 (2018) - [j18]Panos N. Alevizos, Xiao Fu, Nicholas D. Sidiropoulos, Ye Yang, Aggelos Bletsas:
Limited Feedback Channel Estimation in Massive MIMO With Non-Uniform Directional Dictionaries. IEEE Trans. Signal Process. 66(19): 5127-5141 (2018) - [j17]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nicholas D. Sidiropoulos:
Learning to Optimize: Training Deep Neural Networks for Interference Management. IEEE Trans. Signal Process. 66(20): 5438-5453 (2018) - [j16]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos, Ye Yang:
Tensor-Based Channel Estimation for Dual-Polarized Massive MIMO Systems. IEEE Trans. Signal Process. 66(24): 6390-6403 (2018) - [j15]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach. IEEE Trans. Signal Process. 66(24): 6503-6517 (2018) - [c31]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
On Convergence of Epanechnikov Mean Shift. AAAI 2018: 3263-3270 - [c30]Ruiyuan Wu, Chun-Hei Chan, Hoi-To Wai, Wing-Kin Ma, Xiao Fu:
Hi, Bcd! Hybrid Inexact Block Coordinate Descent for Hyperspectral Super-Resolution. ICASSP 2018: 2426-2430 - [c29]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Hyperspectral Super-Resolution Via Coupled Tensor Factorization: Identifiability and Algorithms. ICASSP 2018: 3191-3195 - [c28]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos, Ye Yang:
Tensor-Based Parameter Estimation of Double Directional Massive Mimo Channel with Dual-Polarized Antennas. ICASSP 2018: 3884-3888 - [c27]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Large-Scale Regularized Sumcor GCCA via Penalty-Dual Decomposition. ICASSP 2018: 6363-6367 - [c26]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Hyperspectral Super-Resolution: Combining Low Rank Tensor and Matrix Structure. ICIP 2018: 3318-3322 - [c25]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling. ICML 2018: 2073-2082 - [c24]Mohamed Salah Ibrahim, Ahmed S. Zamzam, Xiao Fu, Nicholas D. Sidiropoulos:
Learning-Based Antenna Selection for Multicasting. SPAWC 2018: 1-5 - [c23]Haoran Sun, Ziping Zhao, Xiao Fu, Mingyi Hong:
Limited Feedback Double Directional Massive MIMO Channel Estimation: From Low-Rank Modeling to Deep Learning. SPAWC 2018: 1-5 - [c22]Ruiyuan Wu, Qiang Li, Xiao Fu, Wing-Kin Ma:
A Convex Low-Rank Regularization Method for Hyperspectral Super-Resolution. SSP 2018: 383-387 - [i15]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
Learning Hidden Markov Models from Pairwise Co-occurrences with Applications to Topic Modeling. CoRR abs/1802.06894 (2018) - [i14]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications. CoRR abs/1803.01257 (2018) - [i13]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. CoRR abs/1804.08806 (2018) - 2017
- [j14]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos:
Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering. IEEE Trans. Signal Process. 65(1): 256-269 (2017) - [j13]John Tranter, Nicholas D. Sidiropoulos, Xiao Fu, Ananthram Swami:
Fast Unit-Modulus Least Squares With Applications in Beamforming. IEEE Trans. Signal Process. 65(11): 2875-2887 (2017) - [j12]Nicholas D. Sidiropoulos, Lieven De Lathauwer, Xiao Fu, Kejun Huang, Evangelos E. Papalexakis, Christos Faloutsos:
Tensor Decomposition for Signal Processing and Machine Learning. IEEE Trans. Signal Process. 65(13): 3551-3582 (2017) - [j11]Xiao Fu, Kejun Huang, Mingyi Hong, Nicholas D. Sidiropoulos, Anthony Man-Cho So:
Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis. IEEE Trans. Signal Process. 65(16): 4150-4165 (2017) - [j10]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos, Lei Huang, Junhao Xie:
Inexact Alternating Optimization for Phase Retrieval in the Presence of Outliers. IEEE Trans. Signal Process. 65(22): 6069-6082 (2017) - [c21]Yanning Shen, Xiao Fu, Georgios B. Giannakis, Nicholas D. Sidiropoulos:
Directed network topology inference via sparse joint diagonalization. ACSSC 2017: 698-702 - [c20]Ahmed S. Zamzam, Xiao Fu, Emiliano Dall'Anese, Nicholas D. Sidiropoulos:
Distributed optimal power flow using feasible point pursuit. CAMSAP 2017: 1-5 - [c19]Ruiyuan Wu, Wing-Kin Ma, Xiao Fu:
A stochastic maximum-likelihood framework for simplex structured matrix factorization. ICASSP 2017: 2557-2561 - [c18]Xiao Fu, Kejun Huang, Mingyi Hong, Nicholas D. Sidiropoulos, Anthony Man-Cho So:
Scalable and flexible Max-Var generalized canonical correlation analysis via alternating optimization. ICASSP 2017: 5855-5859 - [c17]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering. ICML 2017: 3861-3870 - [c16]Xiao Fu, Kejun Huang, Otilia Stretcu, Hyun Ah Song, Evangelos E. Papalexakis, Partha P. Talukdar, Tom M. Mitchell, Nicholas D. Sidiropoulos, Christos Faloutsos, Barnabás Póczos:
BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals. SDM 2017: 216-227 - [c15]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nikos D. Sidiropoulos:
Learning to optimize: Training deep neural networks for wireless resource management. SPAWC 2017: 1-6 - [c14]Panos N. Alevizos, Xiao Fu, Nicholas D. Sidiropoulos, Ye Yang, Aggelos Bletsas:
Non-uniform directional dictionary-based limited feedback for massive MIMO systems. WiOpt 2017: 1-8 - [i12]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nikos D. Sidiropoulos:
Learning to Optimize: Training Deep Neural Networks for Wireless Resource Management. CoRR abs/1705.09412 (2017) - [i11]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos:
On Identifiability of Nonnegative Matrix Factorization. CoRR abs/1709.00614 (2017) - [i10]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
On Convergence of Epanechnikov Mean Shift. CoRR abs/1711.07441 (2017) - [i9]Nikos Kargas, Nicholas D. Sidiropoulos, Xiao Fu:
Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors. CoRR abs/1712.00205 (2017) - [i8]Qingjiang Shi, Mingyi Hong, Xiao Fu, Tsung-Hui Chang:
Penalty Dual Decomposition Method For Nonsmooth Nonconvex Optimization. CoRR abs/1712.04767 (2017) - [i7]Panos N. Alevizos, Xiao Fu, Nicholas D. Sidiropoulos, Ye Yang, Aggelos Bletsas:
Limited Feedback Channel Estimation in Massive MIMO with Non-uniform Directional Dictionaries. CoRR abs/1712.10085 (2017) - 2016
- [j9]Xiao Fu, Wing-Kin Ma:
Robustness Analysis of Structured Matrix Factorization via Self-Dictionary Mixed-Norm Optimization. IEEE Signal Process. Lett. 23(1): 60-64 (2016) - [j8]Xiao Fu, Wing-Kin Ma, José M. Bioucas-Dias, Tsung-Han Chan:
Semiblind Hyperspectral Unmixing in the Presence of Spectral Library Mismatches. IEEE Trans. Geosci. Remote. Sens. 54(9): 5171-5184 (2016) - [j7]Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Power Spectra Separation via Structured Matrix Factorization. IEEE Trans. Signal Process. 64(17): 4592-4605 (2016) - [j6]Xiao Fu, Kejun Huang, Bo Yang, Wing-Kin Ma, Nicholas D. Sidiropoulos:
Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering. IEEE Trans. Signal Process. 64(23): 6254-6268 (2016) - [c13]John H. Tranter, Nicholas D. Sidiropoulos, Xiao Fu, Ananthram Swami:
Fast unit-modulus least squares with applications in transmit beamforming. EUSIPCO 2016: 1378-1382 - [c12]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos, Lei Huang:
Inexact alternating optimization for phase retrieval with outliers. EUSIPCO 2016: 1538-1542 - [c11]Xiao Fu, Wing-Kin Ma, Kejun Huang, Nicholas D. Sidiropoulos:
Robust volume minimization-based matrix factorization via alternating optimization. ICASSP 2016: 2534-2538 - [c10]Xiao Fu, Kejun Huang, Evangelos E. Papalexakis, Hyun Ah Song, Partha Pratim Talukdar, Nicholas D. Sidiropoulos, Christos Faloutsos, Tom M. Mitchell:
Efficient and Distributed Algorithms for Large-Scale Generalized Canonical Correlations Analysis. ICDM 2016: 871-876 - [c9]Kejun Huang, Xiao Fu, Nikos D. Sidiropoulos:
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm. NIPS 2016: 1786-1794 - [i6]Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos, Lei Huang, Junhao Xie:
Inexact Alternating Optimization for Phase Retrieval In the Presence of Outliers. CoRR abs/1605.00973 (2016) - [i5]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos:
Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering. CoRR abs/1605.06711 (2016) - [i4]Nicholas D. Sidiropoulos, Lieven De Lathauwer, Xiao Fu, Kejun Huang, Evangelos E. Papalexakis, Christos Faloutsos:
Tensor Decomposition for Signal Processing and Machine Learning. CoRR abs/1607.01668 (2016) - [i3]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering. CoRR abs/1610.04794 (2016) - [i2]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm. CoRR abs/1611.05010 (2016) - 2015
- [j5]Xiao Fu, Wing-Kin Ma, Tsung-Han Chan, José M. Bioucas-Dias:
Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search Are Related. IEEE J. Sel. Top. Signal Process. 9(6): 1128-1141 (2015) - [j4]Xiao Fu, Wing-Kin Ma, Kejun Huang, Nicholas D. Sidiropoulos:
Blind Separation of Quasi-Stationary Sources: Exploiting Convex Geometry in Covariance Domain. IEEE Trans. Signal Process. 63(9): 2306-2320 (2015) - [j3]Xiao Fu, Kejun Huang, Wing-Kin Ma, Nicholas D. Sidiropoulos, Rasmus Bro:
Joint Tensor Factorization and Outlying Slab Suppression With Applications. IEEE Trans. Signal Process. 63(23): 6315-6328 (2015) - [j2]Xiao Fu, Nicholas D. Sidiropoulos, John H. Tranter, Wing-Kin Ma:
A Factor Analysis Framework for Power Spectra Separation and Multiple Emitter Localization. IEEE Trans. Signal Process. 63(24): 6581-6594 (2015) - [c8]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos:
Joint factor analysis and latent clustering. CAMSAP 2015: 173-176 - [c7]Kejun Huang, Matt Gardner, Evangelos E. Papalexakis, Christos Faloutsos, Nikos D. Sidiropoulos, Tom M. Mitchell, Partha Pratim Talukdar, Xiao Fu:
Translation Invariant Word Embeddings. EMNLP 2015: 1084-1088 - 2014
- [c6]Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma, John Tranter:
Blind spectra separation and direction finding for cognitive radio using temporal correlation-domain ESPRIT. ICASSP 2014: 7749-7753 - [c5]Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Tensor-based power spectra separation and emitter localization for cognitive radio. SAM 2014: 421-424 - [c4]Xiao Fu, Wing-Kin Ma, José M. Bioucas-Dias, Tsung-Han Chan:
A robust subspace method for semiblind dictionary-aided hyperspectral unmixing. WHISPERS 2014: 1-4 - [i1]Xiao Fu, Wing-Kin Ma, Tsung-Han Chan, José M. Bioucas-Dias:
Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search are Related. CoRR abs/1409.4320 (2014) - 2013
- [j1]Ka-Kit Lee, Wing-Kin Ma, Xiao Fu, Tsung-Han Chan, Chong-Yung Chi:
A Khatri-Rao subspace approach to blind identification of mixtures of quasi-stationary sources. Signal Process. 93(12): 3515-3527 (2013) - [c3]Xiao Fu, Wing-Kin Ma, Tsung-Han Chan, José M. Bioucas-Dias, Marian-Daniel Iordache:
Greedy algorithms for pure pixels identification in hyperspectral unmixing: A multiple-measurement vector viewpoint. EUSIPCO 2013: 1-5 - [c2]Xiao Fu, Wing-Kin Ma:
Blind separation of convolutive mixtures of speech sources: Exploiting local sparsity. ICASSP 2013: 4315-4319 - 2012
- [c1]Xiao Fu, Wing-Kin Ma:
A simple closed-form solution for overdetermined blind separation of locally sparse quasi-stationary sources. ICASSP 2012: 2409-2412
Coauthor Index
[i27] [j34] [j33] [j30] [j27] [j26] [j25] [j24] [j23] [j22] [c43] [c38] [c33] [i22] [j21] [j20] [j19] [j18] [j17] [j16] [j15] [c31] [c29] [c28] [c27] [c26] [c25] [c24] [i15] [i14] [i13] [j14] [j13] [j12] [j11] [j10] [c21] [c20] [c18] [c17] [c16] [c15] [c14] [i12] [i11] [i10] [i9] [i7] [j7] [j6] [c13] [c12] [c11] [c10] [c9] [i6] [i5] [i4] [i3] [i2] [j4] [j3] [j2] [c8] [c7] [c6] [c5]
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