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2020 – today
- 2024
[c39]Jingzhou Hu, Kejun Huang:
Complex Bounded Component Analysis: Identifiability and Algorithm. ICASSP 2024: 6680-6684- [c38]Jingzhou Hu, Kejun Huang:
Frank-Wolfe Algorithm for Simplicial and Nonnegative Component Analysis. SAM 2024: 1-5 - [c37]Yuchen Sun, Kejun Huang:
Improved Identifiability and Sample Complexity Analysis of Complete Dictionary Learning. SAM 2024: 1-5 - 2023
- [j23]Danit Shifman Abukasis, Izack Cohen
, Kejun Huang, Xiaochen Xian, Gonen Singer:
An adaptive machine learning algorithm for the resource-constrained classification problem. Eng. Appl. Artif. Intell. 119: 105741 (2023) - [c36]Aysegul Bumin, Megan Shah, Kejun Huang, Tamer Kahveci:
Vulture: VULnerabilities in impuTing drUg REsistance. BCB 2023: 56:1-56:6 - [c35]Jingzhou Hu, Kejun Huang:
Identifiable Bounded Component Analysis Via Minimum Volume Enclosing Parallelotope. ICASSP 2023: 1-5 - [c34]Yuchen Sun, Kejun Huang:
Volume-Regularized Nonnegative Tucker Decomposition with Identifiability Guarantees. ICASSP 2023: 1-5 - [c33]Jingzhou Hu, Kejun Huang:
Global Identifiability of 𝓁1-based Dictionary Learning via Matrix Volume Optimization. NeurIPS 2023 - 2022
- [j22]Aysegul Bumin, Kejun Huang:
Stochastic Douglas-Rachford Splitting for Regularized Empirical Risk Minimization: Convergence, Mini-batch, and Implementation. Trans. Mach. Learn. Res. 2022 (2022) - [c32]Aysegul Bumin, Anna M. Ritz, Donna K. Slonim, Tamer Kahveci, Kejun Huang:
FiT: fiber-based tensor completion for drug repurposing. BCB 2022: 31:1-31:10 - [c31]Yuanfang Ren, Aisharjya Sarkar, Aysegul Bumin, Kejun Huang, Pierangelo Veltri, Alin Dobra, Tamer Kahveci:
Identification of co-existing embeddings of a motif in multilayer networks. BCB 2022: 39:1-39:10 - [c30]Yuchen Sun, Kejun Huang:
HOQRI: Higher-Order QR Iteration for Scalable Tucker Decomposition. ICASSP 2022: 3648-3652 - [i17]Cheng Qian, Kejun Huang, Lucas Glass, Rakshith Sharma Srinivasa, Jimeng Sun:
JULIA: Joint Multi-linear and Nonlinear Identification for Tensor Completion. CoRR abs/2202.00071 (2022) - [i16]Danit Shifman Abukasis, Izack Cohen, Xiaochen Xian, Kejun Huang, Gonen Singer:
Adaptive Learning for the Resource-Constrained Classification Problem. CoRR abs/2207.09196 (2022) - 2021
- [c29]Aysegul Bumin, Kejun Huang:
Efficient Implementation of Stochastic Proximal Point Algorithm for Matrix and Tensor Completion. EUSIPCO 2021: 1050-1054 - 2020
- [j21]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) - [j20]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) - [j19]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Kejun Huang:
Learning Nonlinear Mixtures: Identifiability and Algorithm. IEEE Trans. Signal Process. 68: 2857-2869 (2020) - [c28]Kejun Huang, Xiao Fu:
Low-Complexity Levenberg-Marquardt Algorithm for Tensor Canonical Polyadic Decomposition. ICASSP 2020: 3922-3926 - [c27]Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong:
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems. NeurIPS 2020 - [c26]Bo Yang, Kejun Huang, Nicholas D. Sidiropoulos:
Identifying Potential Investors with Data Driven Approaches. SDM 2020: 235-243 - [i15]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)
2010 – 2019
- 2019
- [j18]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) - [j17]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) - [j16]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) - [c25]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Kejun Huang:
Unsupervised Learning of Nonlinear Mixtures: Identifiability and Algorithm. ACSSC 2019: 1040-1044 - [c24]Guoyong Zhang, Xiao Fu, Kejun Huang, Jun Wang:
Hyperspectral Super-Resolution: A Coupled Nonnegative Block-Term Tensor Decomposition Approach. CAMSAP 2019: 470-474 - [c23]Kejun Huang, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition. DSW 2019: 295-299 - [c22]Kejun Huang, Xiao Fu:
Low-complexity Proximal Gauss-Newton Algorithm for Nonnegative Matrix Factorization. GlobalSIP 2019: 1-5 - [c21]Songtao Lu, Ziping Zhao, Kejun Huang, Mingyi Hong:
Perturbed Projected Gradient Descent Converges to Approximate Second-order Points for Bound Constrained Nonconvex Problems. ICASSP 2019: 5356-5360 - [c20]Xiao Fu, Cheng Gao, Hoi-To Wai, Kejun Huang:
Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization. ICASSP 2019: 7485-7489 - [c19]Kejun Huang, Xiao Fu:
Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm. ICML 2019: 2859-2868 - [c18]Xiao Fu, Kejun Huang:
Block-Term Tensor Decomposition Via Constrained Matrix Factorization. MLSP 2019: 1-6 - [c17]Shahana Ibrahim, Xiao Fu, Nikolaos Kargas, Kejun Huang:
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms. NeurIPS 2019: 7845-7855 - [i14]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Kejun Huang:
Learning Nonlinear Mixtures: Identifiability and Algorithm. CoRR abs/1901.01568 (2019) - [i13]Xiao Fu, Cheng Gao, Hoi-To Wai, Kejun Huang:
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. CoRR abs/1901.05529 (2019) - [i12]Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong:
SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems. CoRR abs/1907.04450 (2019) - [i11]Shahana Ibrahim, Xiao Fu, Nikos Kargas, Kejun Huang:
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms. CoRR abs/1909.12325 (2019) - 2018
- [j15]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos:
On Identifiability of Nonnegative Matrix Factorization. IEEE Signal Process. Lett. 25(3): 328-332 (2018) - [j14]Athanasios P. Liavas, Georgios Kostoulas, Georgios Lourakis, Kejun Huang, Nicholas D. Sidiropoulos:
Nesterov-Based Alternating Optimization for Nonnegative Tensor Factorization: Algorithm and Parallel Implementation. IEEE Trans. Signal Process. 66(4): 944-953 (2018) - [c16]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
On Convergence of Epanechnikov Mean Shift. AAAI 2018: 3263-3270 - [c15]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling. ICML 2018: 2073-2082 - [c14]Shaden Smith, Kejun Huang, Nicholas D. Sidiropoulos, George Karypis:
Streaming Tensor Factorization for Infinite Data Sources. SDM 2018: 81-89 - [i10]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) - [i9]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) - 2017
- [j13]Meiju Li, Xiujuan Du, Kejun Huang, Senlin Hou, Xiuxiu Liu:
A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs). Inf. 8(4): 153 (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) - [c13]Kejun Huang, Nicholas D. Sidiropoulos:
Kullback-Leibler principal component for tensors is not NP-hard. ACSSC 2017: 693-697 - [c12]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 - [c11]Athanasios P. Liavas, Georgios Kostoulas, Georgios Lourakis, Kejun Huang, Nicholas D. Sidiropoulos:
Nesterov-based parallel algorithm for large-scale nonnegative tensor factorization. ICASSP 2017: 5895-5899 - [c10]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 - [i8]Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos:
On Identifiability of Nonnegative Matrix Factorization. CoRR abs/1709.00614 (2017) - [i7]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
On Convergence of Epanechnikov Mean Shift. CoRR abs/1711.07441 (2017) - [i6]Kejun Huang, Nicholas D. Sidiropoulos:
Kullback-Leibler Principal Component for Tensors is not NP-hard. CoRR abs/1711.07925 (2017) - 2016
- [j10]Kejun Huang, Nicholas D. Sidiropoulos, Athanasios P. Liavas:
A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization. IEEE Trans. Signal Process. 64(19): 5052-5065 (2016) - [j9]Cheng Qian, Nicholas D. Sidiropoulos, Kejun Huang, Lei Huang, Hing-Cheung So:
Phase Retrieval Using Feasible Point Pursuit: Algorithms and Cramér-Rao Bound. IEEE Trans. Signal Process. 64(20): 5282-5296 (2016) - [j8]Kejun Huang, Nicholas D. Sidiropoulos:
Consensus-ADMM for General Quadratically Constrained Quadratic Programming. IEEE Trans. Signal Process. 64(20): 5297-5310 (2016) - [j7]Kejun Huang, Yonina C. Eldar, Nicholas D. Sidiropoulos:
Phase Retrieval from 1D Fourier Measurements: Convexity, Uniqueness, and Algorithms. IEEE Trans. Signal Process. 64(23): 6105-6117 (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) - [c9]Xiao Fu, Wing-Kin Ma, Kejun Huang, Nicholas D. Sidiropoulos:
Robust volume minimization-based matrix factorization via alternating optimization. ICASSP 2016: 2534-2538 - [c8]Kejun Huang, Yonina C. Eldar, Nicholas D. Sidiropoulos:
On convexity and identifiability in 1-D Fourier phase retrieval. ICASSP 2016: 3941-3945 - [c7]Cheng Qian, Nicholas D. Sidiropoulos, Kejun Huang, Lei Huang, Hing-Cheung So:
Least squares phase retrieval using feasible point pursuit. ICASSP 2016: 4288-4292 - [c6]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 - [c5]Kejun Huang, Xiao Fu, Nikos D. Sidiropoulos:
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm. NIPS 2016: 1786-1794 - [i5]Kejun Huang, Yonina C. Eldar, Nicholas D. Sidiropoulos:
Phase Retrieval from 1D Fourier Measurements: Convexity, Uniqueness, and Algorithms. CoRR abs/1603.05215 (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]Kejun Huang, Xiao Fu, Nicholas D. Sidiropoulos:
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm. CoRR abs/1611.05010 (2016) - 2015
- [j5]Omar Mehanna, Kejun Huang, Balasubramanian Gopalakrishnan, Aritra Konar, Nicholas D. Sidiropoulos:
Feasible Point Pursuit and Successive Approximation of Non-Convex QCQPs. IEEE Signal Process. Lett. 22(7): 804-808 (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) - [c4]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 - [c3]Kejun Huang, Nicholas D. Sidiropoulos, Athanasios P. Liavas:
Efficient algorithms for 'universally' constrained matrix and tensor factorization. EUSIPCO 2015: 2521-2525 - [c2]Kejun Huang, Nicholas D. Sidiropoulos, Evangelos E. Papalexakis, Christos Faloutsos, Partha Pratim Talukdar, Tom M. Mitchell:
Principled Neuro-Functional Connectivity Discovery. SDM 2015: 631-639 - [i2]Kejun Huang, Nicholas D. Sidiropoulos, Athanasios P. Liavas:
A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization. CoRR abs/1506.04209 (2015) - [i1]Cheng Qian, Nicholas D. Sidiropoulos, Kejun Huang, Lei Huang, Hing-Cheung So:
Phase Retrieval Using Feasible Point Pursuit: Algorithms and Cramér-Rao Bound. CoRR abs/1509.08451 (2015) - 2014
- [j2]Kejun Huang, Nikolaos D. Sidiropoulos:
Putting Nonnegative Matrix Factorization to the Test: A tutorial derivation of pertinent Cramer?Rao bounds and performance benchmarking. IEEE Signal Process. Mag. 31(3): 76-86 (2014) - [j1]Kejun Huang, Nicholas D. Sidiropoulos, Ananthram Swami:
Non-Negative Matrix Factorization Revisited: Uniqueness and Algorithm for Symmetric Decomposition. IEEE Trans. Signal Process. 62(1): 211-224 (2014) - 2013
- [c1]Kejun Huang, Nikos D. Sidiropoulos, A. Swamiy:
NMF revisited: New uniqueness results and algorithms. ICASSP 2013: 4524-4528
Coauthor Index
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