Publications

Check out my Google Scholar page here.

Preprints

  1. H.J.M. Shi, S. Tu, Y. Xu, and W. Yin. A Primer on Coordinate Descent Algorithms.

Journal Publications

  1. J. Luo, K. Shapiro, H.J.M. Shi, Q. Yang, and K. Zhu. Practical Algorithms for Learning Near-Isometric Linear Embeddings. SIAM Undergraduate Research Online, vol. 9, 2016.

Conference Proceedings

  1. R. Bollapragada, D. Mudigere, J. Nocedal, H.J.M. Shi, and P.T.P. Tang. A Progressive Batching L-BFGS Method for Machine Learning. International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018.

  2. H.J.M. Shi, M. Case, X. Gu, S. Tu, and D. Needell. Methods for Quantized Compressed Sensing. Proc. Information Theory and Applications (ITA), La Jolla, CA, Jan. 2016.

Technical Reports

  1. X. Gu, S. Tu, H.J.M. Shi, M. Case, D. Needell, and Y. Plan. Optimizing Quantization for Lasso Recovery. IEEE Signal Processing Letters, Jan. 2018, vol. 25, no. 1, pp. 45-49.

  2. C. Abrahamson, H.J.M. Shi, and B. Yang. Ground Motion Prediction Equations for Arias Intensity Consistent with the NGA-West2 Ground Motion Models. Pacific Earthquake Engineering Research (PEER) Report, July 2016.

Presentations

  1. R. Bollapragada, D. Mudigere, J. Nocedal, H.J.M. Shi, and P.T.P. Tang. A Progressive Batching L-BFGS Method for Machine Learning. Midwest Machine Learning Symposium 2018, Chicago, Illinois, June 2018.

  2. H.J.M. Shi. A Progressive Batching L-BFGS Method for Machine Learning. Chicago Area SIAM Student Conference, Chicago, Illinois, April 2018.

  3. J. Luo, K. Shapiro, H.J.M. Shi, Q. Yang, and K. Zhu. Learning Near-Isometric Linear Embeddings. Joint Mathematics Meetings 2015, San Antonio, Texas, January 2015.