Publications

  1. "Joint NMF for Identification of Shared Features in Datasets and a Dataset Distance Measure"
    by H. Friedman, A. R. Maina-Kilaas, J. Schalkwyk, H. Ahmed, J. Haddock
    Submitted, 2022.
    [ arXiv ]   [ BibTeX ]    [ Code ]

  2. "Nonbacktracking spectral clustering of nonuniform hypergraphs"
    by P. Chodrow, N. Eikmeier, J. Haddock
    Submitted, 2022.
    [ arXiv ]   [ BibTeX ]    [ Code ]

  3. "Paving the Way for Consensus: Convergence of Block Gossip Algorithms"
    by J. Haddock, B. Jarman, C. Yap
    Submitted, 2021.
    [ arXiv ]   [ BibTeX ]

  4. "Statistical Learning for Best Practices in Tattoo Removal"
    by R. Yim, J. Haddock, D. Needell
    Submitted, 2021.
    [ arXiv ]   [ BibTeX ]

  5. "Weakly-Supervised Object Localization using Semi-supervised Nonnegative Matrix Factorization"
    by E. Sizikova, J. Vendrow, R. Grotheer, J. Haddock, L. Kassab, A. Kryshchenko, T. Merkh, M. Rajapaksha, H. V. Vo, C. Wang, K. Leonard, D. Needell
    Submitted. 2020.
    [ BibTeX ]    [ Code ]

  6. "Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling"
    by T. Will, J. Haddock, R. Zhang, D. Molitor, D. Needell, M. Gao, E. Sadovnik
    In preparation. 2019.
    [ arXiv ]    [ BibTeX ]    [ Code ]    [ Slides ]    [ Video ]


  7. Journal Publications

  8. "Quantile-based Iterative Methods for Corrupted Systems of Linear Equations"
    by J. Haddock, D. Needell, E. Rebrova, W. Swartworth
    SIAM Journal on Matrix Analysis and Applications, 43(2), 605-637, 2022.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Code ]

  9. "On Application of Block Kaczmarz Methods in Matrix Factorization"
    by E. Chau, J. Haddock
    SIAM Undergraduate Research Online (SIURO), 2022.
    [ arXiv ]   [ BibTeX ]    [ Code ]

  10. "Greed Works: An Improved Analysis of Sampling Kaczmarz-Motzkin"
    by J. Haddock, A. Ma
    SIAM Journal on Mathematics of Data Science, 3(1), 342-368, 2021.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Slides ]    [ Video ]

  11. "Data-driven Algorithm Selection in Optimization and Signal Processing"
    by J.A. De Loera, J. Haddock, A. Ma, D. Needell
    Annals of Mathematics and Artificial Intelligence, 89(7), 711-735, 2020.
    [ arXiv ]    [ Journal ]    [ BibTeX ]

  12. "Feature Selection on Lyme Disease Patient Survey Data"
    by J. Vendrow, J. Haddock, D. Needell, L. Johnson
    Algorithms, 13(12), 334, 2020.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Code ]

  13. "Antibiotic treatment response in persistent Lyme disease: Why do some patients improve while others do not?"
    by L. Johnson, M. Shapiro, R. Stricker, J. Vendrow, J. Haddock, D. Needell
    Healthcare, vol. 8, no. 4, 383-404, 2020.
    [ Journal ]    [ BibTeX ]

  14. "The Minimum Euclidean-Norm Point on a Convex Polytope: Wolfe's Combinatorial Algorithm is Exponential"
    by J.A. De Loera, J. Haddock, L. Rademacher.
    SIAM Journal on Computing, vol. 49, iss. 1, 138-169, 2019.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Slides ]    [ Video ]

  15. "Randomized Projection Methods for Linear Systems with Arbitrarily Large Sparse Corruptions"
    by J. Haddock, D. Needell
    SIAM Journal on Scientific Computing, vol. 41, iss. 5, S19-S36, 2018.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Slides ]

  16. "On Motzkin's Method for Inconsistent Linear Systems"
    by J. Haddock, D. Needell
    BIT Numerical Mathematics, vol. 59, iss. 2, 387-401, 2019.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Slides ]

  17. "A Sampling Kaczmarz-Motzkin Algorithm for Linear Feasibility"
    by J.A. De Loera, J. Haddock, D. Needell.
    SIAM Journal on Scientific Computing, vol. 39, iss. 5, S66-S87, 2017.
    [ arXiv ]    [ Journal ]    [ BibTeX ]    [ Code ]    [ Slides ]


  18. Conference Publications

  19. "A Generalized Hierarchical Nonnegative Tensor Decomposition"
    by J. Vendrow, J. Haddock, D. Needell
    Proc. Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Singapore, May 2022.
    [ Proceedings ]    [ arXiv ]   [ BibTeX ]   [ Code ]

  20. "Neural Nonnegative CP Decomposition for Hierarchical Tensor Analysis"
    by J. Vendrow, J. Haddock, D. Needell
    Proc. 55th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2021.
    [ BibTeX ]    [ Code ]

  21. "Semi-supervised Nonnegative Matrix Factorization for Document Classification"
    by M. Ahn, R. Grotheer, J. Haddock, L. Kassab, A Kryshchenko, K. Leonard, S. Li, A. Madushani, T. Merkh, D. Needell, E. Sizikova, C. Wang
    Proc. 55th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2021.
    [ arXiv ]    [ BibTeX ]    [ Code ]

  22. "On a Guided Nonnegative Matrix Factorization"
    by J. Vendrow, J. Haddock, E. Rebrova, D. Needell
    Proc. Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, ON, June 2021.
    [ arXiv ]    [ BibTeX ]    [ Code ]

  23. "On Dynamic Topic Modeling with Nonnegative Tensor Decomposition"
    by M. Ahn, N. Eikmeier, J. Haddock, L. Kassab, A. Kryshchenko, K. Leonard, D. Needell, A. Mudiyanselage, E. Sizikova, C. Wang
    Proc. Women in Data Science and Mathematics (WiSDM), Providence, RI, July 2019.
    [ arXiv ]    [ BibTeX ]

  24. "Stochastic Gradient Descent Methods for Corrupted Systems of Linear Equations"
    by J. Haddock, D. Needell, E. Rebrova, W. Swartworth
    Proc. Conference on Information Sciences and Systems (CISS), Princeton, NJ, March 2020.
    [ BibTeX ]    [ Code ]    [ Slides ]

  25. "On Nonnegative CP Tensor Decomposition Robustness to Noise"
    by J. Haddock, L. Kassab, A. Kryshchenko, D. Needell
    Proc. Information Theory and Applications (ITA), San Diego, CA, February 2020.
    [ BibTeX ]

  26. "Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling"
    by M. Gao, J. Haddock, D. Molitor, D. Needell, E. Sadovnik, T. Will, R. Zhang
    Proc. Interational Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Guadeloupe, West Indies, December 2019.
    [ Proceedings ]    [ BibTeX ]    [ Code ]    [ Slides ]    [ Video ]

  27. "Convergence of Iterative Hard Thresholding Variants with Application to Asynchronous Parallel Methods for Sparse Recovery"
    by J. Haddock, D. Needell, N. Rahnavard, A. Zaeemzadeh
    Proc. 53rd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2019.
    [ Proceedings ]    [ BibTeX ]    [ Slides ]

  28. "Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing"
    by J. A. De Loera, J. Haddock, A. Ma, D. Needell
    Proc. International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, August 2019.
    [ BibTeX ]

  29. "On Inferences from Completed Data"
    by J. Haddock, D. Molitor, D. Needell, S. Sambandam, J. Song, S. Sun.
    Proc. Sampling Theory and Applications (SampTA), Bordeaux, France, July 2019.
    [ Proceedings ]    [ BibTeX ]    [ Poster ]

  30. "On Inferences from Completed Data" (extended version)
    by J. Haddock, D. Molitor, D. Needell, S. Sambandam, J. Song, S. Sun.
    Proc. Information Theory and Applications (ITA), San Diego, CA, February 2019.
    [ arXiv ]    [ BibTeX ]    [ Slides ]

  31. "A Bayesian Approach for Asynchronous Parallel Sparse Recovery"
    by A. Zaeemzadeh, J. Haddock, N. Rahnavard, D. Needell.
    Proc. 52nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, October 2018.
    [ Proceedings ]    [ BibTeX ]    [ Poster ]

  32. "The Minimum Euclidean-Norm Point on a Convex Polytope: Wolfe's Combinatorial Algorithm is Exponential"
    by J.A. De Loera, J. Haddock, L. Rademacher.
    Proc. 50th Annual ACM SIGACT Symposium on Theory of Computing, Los Angeles, CA, June 2018.
    [ Proceedings ]    [ BibTeX ]    [ Slides ]    [ Video ]

  33. "Randomized Projections for Corrupted Linear Systems"
    by J. Haddock, D. Needell.
    Proc. 15th Int. Conf. of Numerical Analysis and Applied Mathematics, Rhodes, Greece, Sept. 2017.
    [ BibTeX ]    [ Slides ]


  34. Other Publications

  35. "Projection Algorithms for Convex and Combinatorial Optimization"
    by J. Haddock.
    PhD Dissertation, Applied Mathematics, Univ. of California, Davis, May 2018.
    [ PDF ]    [ BibTeX ]    [ Slides ]