NMF revisited: New uniqueness results and algorithms. - Kejun Huang; Nikos D. Sidiropoulos; A. Swamiy (ICASSP, 2013)

Putting Nonnegative Matrix Factorization to the Test: A tutorial derivation of pertinent Cramer?Rao bounds and performance benchmarking. - Kejun Huang; Nikolaos D. Sidiropoulos (IEEE Signal Process. Mag., 2014)

Non-Negative Matrix Factorization Revisited: Uniqueness and Algorithm for Symmetric Decomposition. - Kejun Huang; Nicholas D. Sidiropoulos; Ananthram Swami (IEEE Trans. Signal Process., 2014)

Translation Invariant Word Embeddings. - Kejun Huang; Matt Gardner 001; Evangelos E. Papalexakis; Christos Faloutsos; Nikos D. Sidiropoulos; Tom M. Mitchell; Partha Pratim Talukdar; Xiao Fu 001 (EMNLP, 2015)

Efficient algorithms for 'universally' constrained matrix and tensor factorization. - Kejun Huang; Nicholas D. Sidiropoulos; Athanasios P. Liavas (EUSIPCO, 2015)

Principled Neuro-Functional Connectivity Discovery. - Kejun Huang; Nicholas D. Sidiropoulos; Evangelos E. Papalexakis; Christos Faloutsos; Partha Pratim Talukdar; Tom M. Mitchell (SDM, 2015)

Feasible Point Pursuit and Successive Approximation of Non-Convex QCQPs. - Omar Mehanna; Kejun Huang; Balasubramanian Gopalakrishnan; Aritra Konar; Nicholas D. Sidiropoulos (IEEE Signal Process. Lett., 2015)

Joint Tensor Factorization and Outlying Slab Suppression With Applications. - Xiao Fu 001; Kejun Huang; Wing-Kin Ma; Nicholas D. Sidiropoulos; Rasmus Bro (IEEE Trans. Signal Process., 2015)

Blind Separation of Quasi-Stationary Sources: Exploiting Convex Geometry in Covariance Domain. - Xiao Fu 001; Wing-Kin Ma; Kejun Huang; Nicholas D. Sidiropoulos (IEEE Trans. Signal Process., 2015)

Robust volume minimization-based matrix factorization via alternating optimization. - Xiao Fu 001; Wing-Kin Ma; Kejun Huang; Nicholas D. Sidiropoulos (ICASSP, 2016)

On convexity and identifiability in 1-D Fourier phase retrieval. - Kejun Huang; Yonina C. Eldar; Nicholas D. Sidiropoulos (ICASSP, 2016)

Least squares phase retrieval using feasible point pursuit. - Cheng Qian 001; Nicholas D. Sidiropoulos; Kejun Huang; Lei Huang 001; Hing-Cheung So (ICASSP, 2016)

Efficient and Distributed Algorithms for Large-Scale Generalized Canonical Correlations Analysis. - Xiao Fu 001; Kejun Huang; Evangelos E. Papalexakis; Hyun Ah Song; Partha Pratim Talukdar; Nicholas D. Sidiropoulos; Christos Faloutsos; Tom M. Mitchell (ICDM, 2016)

Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm. - Kejun Huang; Xiao Fu 001; Nikos D. Sidiropoulos (NIPS, 2016)

Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering. - Xiao Fu 001; Kejun Huang; Bo Yang; Wing-Kin Ma; Nicholas D. Sidiropoulos (IEEE Trans. Signal Process., 2016)

Phase Retrieval from 1D Fourier Measurements: Convexity, Uniqueness, and Algorithms. - Kejun Huang; Yonina C. Eldar; Nicholas D. Sidiropoulos (IEEE Trans. Signal Process., 2016)

Consensus-ADMM for General Quadratically Constrained Quadratic Programming. - Kejun Huang; Nicholas D. Sidiropoulos (IEEE Trans. Signal Process., 2016)

A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization. - Kejun Huang; Nicholas D. Sidiropoulos; Athanasios P. Liavas (IEEE Trans. Signal Process., 2016)

Phase Retrieval Using Feasible Point Pursuit: Algorithms and Cramér-Rao Bound. - Cheng Qian 001; Nicholas D. Sidiropoulos; Kejun Huang; Lei Huang 001; Hing-Cheung So (IEEE Trans. Signal Process., 2016)

Kullback-Leibler principal component for tensors is not NP-hard. - Kejun Huang; Nicholas D. Sidiropoulos (ACSSC, 2017)

Scalable and flexible Max-Var generalized canonical correlation analysis via alternating optimization. - Xiao Fu 001; Kejun Huang; Mingyi Hong 001; Nicholas D. Sidiropoulos; Anthony Man-Cho So (ICASSP, 2017)

Nesterov-based parallel algorithm for large-scale nonnegative tensor factorization. - Athanasios P. Liavas; Georgios Kostoulas; Georgios Lourakis; Kejun Huang; Nicholas D. Sidiropoulos (ICASSP, 2017)

BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals. - Xiao Fu 001; Kejun Huang; Otilia Stretcu; Hyun Ah Song; Evangelos E. Papalexakis; Partha P. Talukdar; Tom M. Mitchell; Nicholas D. Sidiropoulos; Christos Faloutsos; Barnabás Póczos (SDM, 2017)

A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs). - Meiju Li; Xiujuan Du; Kejun Huang; Senlin Hou; Xiuxiu Liu (Inf., 2017)

Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis. - Xiao Fu 001; Kejun Huang; Mingyi Hong 001; Nicholas D. Sidiropoulos; Anthony Man-Cho So (IEEE Trans. Signal Process., 2017)

Tensor Decomposition for Signal Processing and Machine Learning. - Nicholas D. Sidiropoulos; Lieven De Lathauwer; Xiao Fu 001; Kejun Huang; Evangelos E. Papalexakis; Christos Faloutsos (IEEE Trans. Signal Process., 2017)

On Convergence of Epanechnikov Mean Shift. - Kejun Huang; Xiao Fu 001; Nicholas D. Sidiropoulos (AAAI, 2018)

Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling. - Kejun Huang; Xiao Fu 001; Nicholas D. Sidiropoulos (ICML, 2018)

Streaming Tensor Factorization for Infinite Data Sources. - Shaden Smith; Kejun Huang; Nicholas D. Sidiropoulos; George Karypis (SDM, 2018)

Learning Hidden Markov Models from Pairwise Co-occurrences with Applications to Topic Modeling. - Kejun Huang; Xiao Fu 001; Nicholas D. Sidiropoulos (CoRR, 2018)

On Identifiability of Nonnegative Matrix Factorization. - Xiao Fu 001; Kejun Huang; Nicholas D. Sidiropoulos (IEEE Signal Process. Lett., 2018)

Nesterov-Based Alternating Optimization for Nonnegative Tensor Factorization: Algorithm and Parallel Implementation. - Athanasios P. Liavas; Georgios Kostoulas; Georgios Lourakis; Kejun Huang; Nicholas D. Sidiropoulos (IEEE Trans. Signal Process., 2018)

Unsupervised Learning of Nonlinear Mixtures: Identifiability and Algorithm. - Bo Yang; Xiao Fu 001; Nicholas D. Sidiropoulos; Kejun Huang (ACSSC, 2019)

Hyperspectral Super-Resolution: A Coupled Nonnegative Block-Term Tensor Decomposition Approach. - Guoyong Zhang; Xiao Fu 001; Kejun Huang; Jun Wang 005 (CAMSAP, 2019)

Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition. - Kejun Huang; Zhuoran Yang; Zhaoran Wang 001; Mingyi Hong 001 (DSW, 2019)

Low-complexity Proximal Gauss-Newton Algorithm for Nonnegative Matrix Factorization. - Kejun Huang; Xiao Fu 001 (GlobalSIP, 2019)

Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization. - Xiao Fu 001; Cheng Gao; Hoi-To Wai; Kejun Huang (ICASSP, 2019)

Perturbed Projected Gradient Descent Converges to Approximate Second-order Points for Bound Constrained Nonconvex Problems. - Songtao Lu; Ziping Zhao 002; Kejun Huang; Mingyi Hong 001 (ICASSP, 2019)

Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm. - Kejun Huang; Xiao Fu 001 (ICML, 2019)

Block-Term Tensor Decomposition Via Constrained Matrix Factorization. - Xiao Fu 001; Kejun Huang (MLSP, 2019)

Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms. - Shahana Ibrahim; Xiao Fu 001; Nikolaos Kargas; Kejun Huang (NeurIPS, 2019)

Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. - Xiao Fu 001; Cheng Gao; Hoi-To Wai; Kejun Huang (CoRR, 2019)

SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems. - Songtao Lu; Meisam Razaviyayn; Bo Yang; Kejun Huang; Mingyi Hong 001 (CoRR, 2019)

Anchor-Free Correlated Topic Modeling. - Xiao Fu 001; Kejun Huang; Nicholas D. Sidiropoulos; Qingjiang Shi; Mingyi Hong 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications. - Xiao Fu 001; Kejun Huang; Nicholas D. Sidiropoulos; Wing-Kin Ma (IEEE Signal Process. Mag., 2019)

Efficient and Distributed Generalized Canonical Correlation Analysis for Big Multiview Data. - Xiao Fu 001; Kejun Huang; Evangelos E. Papalexakis; Hyun Ah Song; Partha P. Talukdar; Nicholas D. Sidiropoulos; Christos Faloutsos; Tom M. Mitchell (IEEE Trans. Knowl. Data Eng., 2019)

Low-Complexity Levenberg-Marquardt Algorithm for Tensor Canonical Polyadic Decomposition. - Kejun Huang; Xiao Fu 001 (ICASSP, 2020)

Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems. - Songtao Lu; Meisam Razaviyayn; Bo Yang; Kejun Huang; Mingyi Hong 001 (NeurIPS, 2020)

Identifying Potential Investors with Data Driven Approaches. - Bo Yang; Kejun Huang; Nicholas D. Sidiropoulos (SDM, 2020)

Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors. - Xiao Fu 001; Nico Vervliet; Lieven De Lathauwer; Kejun Huang; Nicolas Gillis (CoRR, 2020)

Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective. - Xiao Fu 001; Nico Vervliet; Lieven De Lathauwer; Kejun Huang; Nicolas Gillis (IEEE Signal Process. Mag., 2020)

Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization. - Xiao Fu 001; Shahana Ibrahim; Hoi-To Wai; Cheng Gao; Kejun Huang (IEEE Trans. Signal Process., 2020)

Learning Nonlinear Mixtures: Identifiability and Algorithm. - Bo Yang; Xiao Fu 001; Nicholas D. Sidiropoulos; Kejun Huang (IEEE Trans. Signal Process., 2020)

Efficient Implementation of Stochastic Proximal Point Algorithm for Matrix and Tensor Completion. - Aysegul Bumin; Kejun Huang (EUSIPCO, 2021)

FiT: fiber-based tensor completion for drug repurposing. - Aysegul Bumin; Anna M. Ritz; Donna K. Slonim; Tamer Kahveci; Kejun Huang (BCB, 2022)

Identification of co-existing embeddings of a motif in multilayer networks. - Yuanfang Ren; Aisharjya Sarkar; Aysegul Bumin; Kejun Huang; Pierangelo Veltri; Alin Dobra; Tamer Kahveci (BCB, 2022)

HOQRI: Higher-Order QR Iteration for Scalable Tucker Decomposition. - Yuchen Sun; Kejun Huang (ICASSP, 2022)

JULIA: Joint Multi-linear and Nonlinear Identification for Tensor Completion. - Cheng Qian 001; Kejun Huang; Lucas Glass; Rakshith Sharma Srinivasa; Jimeng Sun 001 (CoRR, 2022)

Adaptive Learning for the Resource-Constrained Classification Problem. - Danit Shifman Abukasis; Izack Cohen; Xiaochen Xian; Kejun Huang; Gonen Singer (CoRR, 2022)

Stochastic Douglas-Rachford Splitting for Regularized Empirical Risk Minimization: Convergence, Mini-batch, and Implementation. - Aysegul Bumin; Kejun Huang (Trans. Mach. Learn. Res., 2022)

Vulture: VULnerabilities in impuTing drUg REsistance. - Aysegul Bumin; Megan Shah; Kejun Huang; Tamer Kahveci (BCB, 2023)

Identifiable Bounded Component Analysis Via Minimum Volume Enclosing Parallelotope. - Jingzhou Hu; Kejun Huang (ICASSP, 2023)

Volume-Regularized Nonnegative Tucker Decomposition with Identifiability Guarantees. - Yuchen Sun; Kejun Huang (ICASSP, 2023)

PartialFibers: An Efficient Method for Predicting Drug-Drug Interactions. - Aysegul Bumin; Kejun Huang; Tamer Kahveci (ICCABS, 2023)

Global Identifiability of 𝓁1-based Dictionary Learning via Matrix Volume Optimization. - Jingzhou Hu; Kejun Huang (NeurIPS, 2023)

An adaptive machine learning algorithm for the resource-constrained classification problem. - Danit Shifman Abukasis; Izack Cohen; Kejun Huang; Xiaochen Xian; Gonen Singer (Eng. Appl. Artif. Intell., 2023)

Complex Bounded Component Analysis: Identifiability and Algorithm. - Jingzhou Hu; Kejun Huang (ICASSP, 2024)

Frank-Wolfe Algorithm for Simplicial and Nonnegative Component Analysis. - Jingzhou Hu; Kejun Huang (SAM, 2024)

Improved Identifiability and Sample Complexity Analysis of Complete Dictionary Learning. - Yuchen Sun; Kejun Huang (SAM, 2024)

Global Identifiability of Overcomplete Dictionary Learning via L1 and Volume Minimization. - Yuchen Sun; Kejun Huang (ICLR, 2025)