You can find representative papers categorized by topics under Research. My Google Scholar profile sometimes is more up-to-date. Accompanying codes can be downloaded next to the link of the papers when available.

Preprints



Tutorials and Overview Articles



Journals


  1. Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization [Arxiv]
    Y. Chen, Y. Chi, J. Fan, C. Ma and Y. Yan, SIAM Journal on Optimization, accepted.

  2. Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion [Arxiv]
    K. Ji, J. Tan, J. Xu, and Y. Chi, IEEE Trans. on Signal Processing, accepted.

  3. Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction [Arxiv] [Code]
    B. Li, S. Cen, Y. Chen, and Y. Chi, Journal of Machine Learning Research, accepted with minor revisions.

  4. Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data [Arxiv]
    S. Cen, H. Zhang, Y. Chi, W. Chen and T.-Y. Liu, IEEE Trans. on Signal Processing, in press.

  5. Subspace Estimation from Unbalanced and Incomplete Data Matrices: $\ell_{2,\infty}$ Statistical Guarantees [Arxiv]
    C. Cai, G. Li, Y. Chi, H. V. Poor, and Y. Chen, Annals of Statistics, accepted.

  6. On the Stable Resolution Limit of Total Variation Regularization for Spike Deconvolution [Arxiv]
    M. Ferreira Da Costa and Y. Chi, IEEE Trans. on Information Theory, in press.

  7. Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy [Arxiv]
    H. Fu, Y. Chi, and Y. Liang, IEEE Trans. on Signal Processing, vol. 68, pp. 3225-3235, 2020.

  8. Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent [Arxiv]
    Y. Li, Y. Chi, H. Zhang, and Y. Liang, Information and Inference: A Journal of the IMA, vol. 9, no. 2, pp. 289-325, 2020.

  9. Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion and Blind Deconvolution [Main] [Supplementary] [Full] [Arxiv]
    C. Ma, K. Wang, Y. Chi, and Y. Chen, Foundations of Computational Mathematics, vol. 20, pp. 451-632, 2020.

  10. Analytical Convergence Regions of Accelerated Gradient Descent in Nonconvex Optimization under Regularity Condition [Arxiv]
    H. Xiong, Y. Chi, B. Hu, and W. Zhang, Automatica, vol. 113, pp. 108715, 2020.

  11. Vector-Valued Graph Trend Filtering with Non-Convex Penalties [Arxiv] [Code]
    R. Varma*, H. Lee*, J. Kovacevic and Y. Chi, IEEE Trans. on Signal Processing over Networks, vol. 6, no. 1, pp. 48-62, 2020. (*=equal contribution)

  12. Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval [Main] [Supplementary] [Arxiv]
    Y. Chen, Y. Chi, J. Fan and C. Ma, Mathematical Programming, vol. 176, no. 1, pp. 5-37, 2019.

  13. Low-Rank Structured Covariance Matrix Estimation [Code]
    A. P. Shikhaliev, L. C. Potter and Y. Chi, IEEE Signal Processing Letters, vol. 26, no. 5, pp. 700-704, 2019.

  14. Stable Separation and Super-Resolution of Mixture Models [Arxiv]
    Y. Li and Y. Chi, Applied and Computational Harmonic Analysis, vol. 46, no. 1, pp. 1-39, 2019.

  15. Median-Truncated Nonconvex Approach for Phase Retrieval with Outliers [Arxiv]
    H. Zhang, Y. Chi and Y. Liang, IEEE Trans. on Information Theory, vol. 64, no. 11, pp. 7287-7310, 2018.

  16. Quantized Spectral Compressed Sensing: Cramer-Rao Bounds and Recovery Algorithms [Arxiv]
    H. Fu and Y. Chi, IEEE Trans. on Signal Processing, vol. 66, no. 12, pp. 3268-3279, 2018.

  17. Stochastic Approximation and Memory-Limited Subspace Tracking for Poisson Streaming Data [PDF]
    L. Wang and Y. Chi, IEEE Trans. on Signal Processing, vol. 66, no. 4, pp. 1051-1064, 2018.

  18. A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms [Code]
    H. Zhang, Y. Zhou, Y. Liang and Y. Chi, Journal of Machine Learning Research, vol. 18, no. 141, pp. 1-35, 2017.

  19. Subspace Learning From Bits [Arxiv]
    Y. Chi and H. Fu, IEEE Trans. on Signal Processing, vol. 65, no. 17, pp. 4429-4442, 2017.

  20. Super-Resolution Image Reconstruction for High-Density 3D Single-Molecule Microscopy [PDF] [Code]
    J. Huang, M. Sun, J. Ma and Y. Chi, IEEE Trans. on Computational Imaging, vol. 3, no. 4, pp. 763-773, 2017.

  21. Low-Rank Positive Semidefinite Matrix Recovery from Corrupted Rank-One Measurements [Arxiv]
    Y. Li, Y. Sun and Y. Chi, IEEE Trans. on Signal Processing, vol. 65, no. 2, pp. 397-408, 2017.

  22. Blind Deconvolution from Multiple Sparse Inputs [Extended]
    L. Wang and Y. Chi, IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1384-1388, 2016.

  23. Kaczmarz Method for Solving Quadratic Equations
    Y. Chi and Y. M. Lu, IEEE Signal Processing Letters, vol. 23, no. 9, pp. 1183 - 1187, 2016.

  24. Guaranteed Blind Sparse Spikes Deconvolution via Lifting and Convex Optimization [Arxiv] [Code]
    Y. Chi, IEEE Journal of Selected Topics in Signal Processing - Special Issue on Structured Matrices in Signal and Data Processing, vol. 10, no. 4, pp. 782 - 794, 2016.

  25. Off-the-Grid Line Spectrum Denoising and Estimation with Multiple Measurement Vectors [Arxiv] [Code]
    Y. Li and Y. Chi, IEEE Trans. on Signal Processing, vol. 64, pp. 1257 - 1269, 2016.

  26. Orthogonal Matching Pursuit on Faulty Circuits
    Y. Li, Y. Chi, C-H Huang, and L. Dolecek, IEEE Trans. on Communications, vol. 63, pp. 2541 - 2554, 2015.

  27. Fast Two-dimensional Super-resolution Image Reconstruction Algorithm for Ultra-high Emitter Density [Code]
    J. Huang, K. Gumpper, Y. Chi, M. Sun and J. Ma, Optics Letters, vol. 40, pp. 2989 - 2992, 2015.

  28. Exact and Stable Covariance Estimation from Quadratic Sampling via Convex Programming [Arxiv]
    Y. Chen, Y. Chi and A. J. Goldsmith. IEEE Trans. on Information Theory, vol. 61, pp. 4034 - 4059, 2015.

  29. 3D Multifocus Astigmatism and Compressed Sensing (3D MACS) Based Superresolution Reconstruction [Code]
    J. Huang, M. Sun, K. Gumpper, Y. Chi and J. Ma. Biomedical Optics Express, vol. 6, pp. 902 - 917, 2015.

  30. Compressive Two-Dimensional Harmonic Retrieval via Atomic Norm Minimization [Code]
    Y. Chi and Y. Chen. IEEE Trans. on Signal Processing, vol. 63, pp. 1030 - 1042, 2015.

  31. Robust Spectral Compressed Sensing via Structured Matrix Completion [Arxiv] [Code]
    Y. Chen and Y. Chi. IEEE Trans. on Information Theory, vol. 60, pp. 6576-6601, 2014.

  32. Classification and Boosting with Multiple Collaborative Representations
    Y. Chi and F. Porikli. IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 36, pp. 1519 - 1531, 2014.

  33. Resolving Spatial Modes of Lasers via Matrix Completion
    Y. Chi and B. L. Anderson. Optics Letters, vol. 38, pp. 3957 - 3960, 2013.

  34. PETRELS: Parallel Subspace Estimation and Tracking using Recursive Least Squares from Partial Observations [Code]
    Y. Chi, Y. C. Eldar, and R. Calderbank. IEEE Trans. on Signal Processing, vol. 61, pp. 5947 - 5959, 2013.

  35. Sensitivity of Basis Mismatch to Compressed Sensing [Young Author Best Paper Award]
    Y. Chi, L. L. Scharf, A. Pezeshki and R. Calderbank. IEEE Trans. on Signal Processing, vol. 59, pp. 2182 - 2195, 2011.

  36. Training Signal Design and Tradeoffs for Spectrally-Efficient Multi-User MIMO-OFDM Systems
    Y. Chi, A. Gomaa, N. Al-Dhahir and R. Calderbank. IEEE Trans. on Wireless Communications, vol. 10, pp. 2234 - 2245, 2011.


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