Kejun Huang

Contact Information:
Department of Electrical and Computer Engineering
University of Minnesota, Twin Cities
117 Pleasant St. SE, Minneapolis, MN, 55455

Office: 468 Walter Library
E-mail: huang663 [at] umn [dot] edu




I am a Postdoctoral Associate in the Department Electrical and Computer Engineering at University of Minnesotaand affiliated to the Digital Technology Center . I am with the Signal and Tensor Analytics Research (STAR) group, under the supervision of  Professor Nikos Sidiropoulos. My research interests include signal processing, machine learning, big data analytics, and optimization.

Curriculum vitae: CV.pdf

Publications: 
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Journal:
  1. X. Fu*, K. Huang*, and N. D. Sidiropoulos, “On Identifiability of Nonnegative Matrix Factorization”, IEEE Signal Processing Letter, Dec. 2017 (accepted). arxiv
  2. A. P. Liavas, G. Kostouloas, G. Lourakis, K. Huang, and N. D. Sidiropoulos, “Nesterov-based Alternating Optimization for Nonnegative Tensor Factorization: Algorithm and Parallel Implementation”, IEEE Transactions on Signal Processing, Nov. 2017 (accepted).
  3. X. Fu, K. Huang, M. Hong, N. D. Sidiropoulos, and A. M.-C. So, “Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis”, IEEE Transactions on Signal Processing, 65(16):4150-4165, Aug. 2017. doi arxiv
  4. N. D. Sidiropoulos, L. De Lathauwer, X. Fu, K. Huang, E. E. Papalexakis, and C. Faloutsos, “Tensor Decomposition for Signal Processing and Machine Learning”, IEEE Transactions on Signal Processing, 65(13):3551-3582, July 2017. doi arxiv
  5. X. Fu, K. Huang, B. Yang, W.-K. Ma, and N. D. Sidiropoulos, “Robust Volume Minimization-based Matrix Factorization for Remote Sensing and Document Clustering”, IEEE Transactions on Signal Processing, 64(23):6254-6268, Dec. 2016. doi arxiv
  6. K. Huang, Y. C. Eldar, and N. D. Sidiropoulos, “Phase Retrieval from 1D Fourier Measurements: Convexity, Uniqueness, and Algorithms”, IEEE Transactions on Signal Processing, 64(23): 6105-6117, Dec. 2016. doi arxiv
  7. K. Huang and N. D. Sidiropoulos, Consensus-ADMM for General Quadratically Constrained Quadratic Programming”, IEEE Transactions on Signal Processing, 64(20):5297-5310, Oct. 2016. doi arxiv
  8. C. Qian, N. D. Sidiropoulos, K. Huang, L. Huang, and H.-C. So, “Phase Retrieval Using Feasible Point Pursuit: Algorithms and Cramer-Rao Bound”, IEEE Transactions on Signal Processing, 64(20):5282-5296, Oct. 2016. doi arxiv
  9. K. Huang, N. D. Sidiropoulos, and A. P. Liavas, “A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor FactorizationIEEE Transactions on Signal Processing, 64(19):5052-5065, Oct. 2016. doi arxiv matlab
  10. X. Fu, K. Huang, W.-K. Ma, N. D. Sidiropoulos, and R. Bro, “Joint Tensor Factorization and Outlying Slab Suppression with Applications”, IEEE Transactions on Signal Processing, 63(23):6315-6328, Dec. 2015. doi arxiv
  11. O. Mehanna, K. Huang, B. Gopalakrishnan, A. Konar, and N. D. Sidiropoulos, “Feasible Point Pursuit and Successive Approximation of Non-convex QCQPs”, IEEE Signal Processing Letter, 22(7):804-808, July 2015. doi arxiv
  12. X. Fu, W.-K. Ma, K. Huang, and N. D. Sidiropoulos, “Blind Separation of Quasi-stationary Sources: Exploiting Convex Geometry in Covariance Domain”, IEEE Transactions on Signal Processing, 63(9):2306-2320, June 2015. doi
  13. K. Huang, and N. D. Sidiropoulos, “Putting NMF to the Test: A Tutorial Derivation of Pertinent Cramer-Rao Bounds and Performance Benchmarking”, IEEE Signal Processing Magazine, special issue on Source Separation and its Applications, 31(3):76-86, May, 2014. doi
  14. K. Huang, N. D. Sidiropoulos, and A. Swami, “Non-negative Matrix Factorization Revisited: Uniqueness and Algorithm for Symmetric Decomposition”, IEEE Transactions on Signal Processing, 62(1):211-224, Jan., 2014. doi
Conference (Computer Science):
  1. S. Smith*, K. Huang*, N. D. Sidiropoulos, and G. Karypis, “Streaming Tensor Factorization for Infinite Data Sources”, in SIAM International Conference on Data Mining (SDM), 2018, San Diego, CA (acceptance rate: 23.2%).
  2. K. Huang, X. Fu, and N. D. Sidiropoulos, “On Convergence of Epanechnikov Mean Shift”, in AAAI Conference on Artificial Intelligence (AAAI), 2018, New Orleans, LA (acceptance rate: 25%). arxiv
  3. X. Fu, K. Huang, O. Stretcu, H. Song, E. E. Papalexakis, P. P. Talukdar, T. Mitchell, N. D. Sidiropoulos, C. Faloutsos, and B. Poczos, “BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals”, in SIAM International Conference on Data Mining (SDM), 2017, Houston, TX (acceptance rate: 26%). doi
  4. X. Fu, K. Huang, E. E. Papalexakis, H. Song, P. P. Talukdar, N. D. Sidiropoulos, C. Faloutsos, and T. Mitchell, “Efficient and Distributed Algorithms for Large-Scale Generalized Canonical Correlation Analysis”, in IEEE International Conference on Data Mining (ICDM), 2016, Barcelona, Spain (acceptance rate: 19.6%). doi
  5. K. Huang*, X. Fu*, and N. D. Sidiropoulos, “Anchor-free Correlated Topic Modeling: Identifiability and Algorithm”, in Conference on Neural Information Processing Systems (NIPS), 2016, Barcelona, Spain (acceptance rate: 22.7%). doi arxiv
  6. M. Gardner*, K. Huang*, E. E. Papalexakis, X. Fu, P. P. Talukdar, C. Faloutsos, N. D. Sidiropoulos, and T. Mitchell, “Translation Invariant Word Embeddings”, in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2015, Lisbon, Portugal (acceptance rate: 23.7%). doi matlab data
  7. K. Huang, N. D. Sidiropoulos, E. E. Papalexakis, C. Faloutsos, P. P. Talukda, and T. Mitchell, “Principled Neuro-Functional Connectivity Discovery”, in SIAM International Conference on Data Mining (SDM), 2015, Vancouver, Canada (oral presentation, acceptance rate: 14.7%). doi
Conference (Signal Processing):
  1. K. Huang and N. D. Sidiropoulos, “Kullback-Leibler Principal Component for Tensors is not NP-hard”, in Asilomar Conference on Signals, Systems, and Computers (Asilomar), 2017, Pacific Grove, CA. arxiv
  2. K. Huang and Y. C. Eldar, “Phase Retrieval Using a Conjugate Symmetric Reference”, in International Conference on Sampling Theory and Applications (SampTA), 2017, Tallinn, Estonia. doi
  3. X. Fu, K. Huang, M. Hong, N. D. Sidiropoulos, and A. M.-C. So, “Scalable and Flexible MAX-VAR Generalized Canonical Correlation Analysis via Alternating Optimization”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017, New Orleans, LA. doi
  4. A. P. Liavas, G. Kostoulas, G. Lourakis, K. Huang, and N. D. Sidiropoulos, “Nesterov-based Parallel Algorithm for Large-scale Nonnegative Tensor Factorization”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017, New Orleans, LA. doi
  5. K. Huang, Y. C. Eldar, and N. D. Sidiropoulos, On Convexity and Identifiability in 1-D Fourier Phase Retrieval”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, Shanghai, China. doi
  6. X. Fu, W.-K. Ma, K. Huang, and N. D. Sidiropoulos, Robust Volume Minimization-based Matrix Factorization via Alternating Optimization”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, Shanghai, China. doi
  7. C. Qian, N. D. Sidiropoulos, K. Huang, L. Huang, and H.-C. So, Least Squares Phase Retrieval Using Feasible Point Pursuit”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, Shanghai, China. doi
  8. K. Huang, N. D. Sidiropoulos, and A. P. Liavas, “Efficient Algorithms for 'Universally' Constrained Matrix and Tensor Factorization”, in European Signal Processing Conference (EUSIPCO), 2015, Nice, France. doi
  9. K. Huang, N. D. Sidiropoulos, and A. Swami, “NMF Revisited: New Uniqueness Results and Algorithms”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013, Vancouver, Canada. doi