Contingency tables, Random Matrices, Optimal Transport

  1. Hanbaek Lyu and Sumit Muhkerjee, “Large random matrices with given margins.” Submitted. Prepint  (2024) (Last updated ver: Aug 6, 2025 CT_limit)
  2. Rahul Choudhary and Hanbaek Lyu, “Linear convergence of Sinkhorn’s algorithm for generalized static Schrödinger bridge“, To appear in ICML 2025 (OpenReview)
  3. Yulia Alexandr, Miles Bakenhus, Mark Curiel, Sameer K. Deshpande, Elizabeth Gross, Yuqi Gu, Max Hill, Joseph Johnson, Bryson Kagy, Vishesh Karwa, Jiayi Li, Hanbaek Lyu, Sonja Petrović, Jose Israel Rodriguez, “New directions in algebraic statistics: Three challenges from 2023.”  Algebraic Statistics. Vol. 15 (2024), No. 2, 357–382 (Preprint) 
  4. Hanbaek Lyu and Igor Pak, “On the number of contingency tables and the independence heuristic.” Bulletin of the London Mathematical Society 54 (1), 242-255, 2022 (Journal, Preprint)
  5. Sam Dittmer, Hanbaek Lyu, and Igor Pak, “Phase transition in random contingency tables with non-uniform margins.” Trans. Amer. Math. Soc. 373 (2020), pp. 8313-8338. (Journal, Preprint)                     

 

Solitons and Box-ball Systems

  1. David Keating, Minjun Kim, Eva Loeser, Hanbaek Lyu, “Diffusive Scaling limit of stochastic Box-Ball systems and PushTASEP.”  Preprint 2025
  2. Joel Lewis, Hanbaek Lyu, Pavlo Pylyavskyy, and Arnab Sen, “Scaling limit of soliton lengths in a multicolor box-ball system.” Forum of Mathematics, Sigma, Vol 12, 2024 e120 doi:10.1017/fms.2024.74 (Journal) 
  3. Atsuo Kuniba, Hanbaek Lyu, and Masato Okado, “Randomized box-ball systems, limit shape of rigged configurations and Thermodynamic Bethe ansatz.” Nuclear Physics B (2018). (Journal, Preprint)
  4. Atsuo Kuniba and Hanbaek Lyu, “Large deviations and one-sided scaling limit of multicolor box-ball system”. Journal of Statistical Physics, 178(1), 38-74. (Journal, Preprint)
  5. Lionel Levine, Hanbaek Lyu, and John Pike, “Double jump phase transition in a soliton cellular automaton.” International Mathematics Research Notices, Volume 2022, Issue 1, January 2022, Pages 665–727  (Journal, Preprint)                                           

Optimization, Machine Learning, and Networks

  1. William Powell, Jeongyeol Kwon, Qiaomin Xie, and Hanbaek Lyu “Offline Actor-Critic for Average Reward MDPs”, To appear in NeurIPS 2025
  2. David Clancy Jr., Hanbaek Lyu, and Sebastien Roch, “Sample complexity of branch-length estimation by maximum likelihood”, To appear in ICML 2025
  3. Hanbaek Lyu and Yuchen Li, “Block majorization-minimization with diminishing radius for constrained nonconvex optimization.”  SIAM Journal on Optimization, Vol. 35, Iss. 2 (2025)  [Journal, Preprint, GitHub, FreePDF: BMM_SIOPT] 
  4. Hanbaek Lyu, “Stochastic regularized block majorization-minimization with weakly convex and multi-convex surrogates” Journal of Machine Learning Research, 25(306):1−83, 2024 [Journal, GitHub]
  5. Danny Duan and Hanbaek Lyu, “A fast and efficient randomized quasi-Newton method“, To appear in NeurIPS 2024 Workshop on Optimization for Machine Learning
  6. Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizabeta Rebrova, and Jiahong Yuan, “Detecting Short-lasting Topics Using Nonnegative Tensor Decomposition” Front. Appl. Math. Stat., 22 July 2024 Sec. Optimization (Journal)
  7. Joowon Lee, Hanbaek Lyu, and Weixin Yao, “Supervised Matrix Factorization: Local Landscape Analysis and Applications ” ICML 2024 (Paper, SMF_poster_ICML2024)
  8. Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu, “On the Complexity of First-Order Methods in Stochastic Bilevel Optimization.” ICML 2024 (Paper, bilevel_poster)
  9. William Powell and Hanbaek Lyu, “Stochastic optimization with arbitrary recurrent data sampling.” ICML 2024 (Preprint, Paper) 
  10. Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu, “Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms.” ICML 2024  (Preprint, Paper)
  11. Keunsu Kim, Hanbaek Lyu, Jinsu Kim, Jae-Hun Jung, “Supervised low-rank semi-nonnegative matrix factorization with frequency regularization for forecasting spatio-temporal data.” Journal of Scientific Computing, 100, 29 (2024) (Preprint, Journal)
  12. Jianhao Peng, Chao Pan, Hanbaek Lyu, Minji Kim, Albert Cheng, and Olgica Milenkovic, “Inferring Single-Molecule Chromatin Interactions via Online Convex Network Dictionary Learning” PLOS Computational Biology, 20(5): e1012095 (2024) (Journal, Preprint)
  13. Joowon Lee, Hanbaek Lyu, and Weixin Yao, “Exponentially Convergent Algorithms for Supervised Matrix Factorization“, NeurIPS 2023 [Paper, Preprint]
  14. Hanbaek Lyu, Yacoub Kureh, Joshua Vendrow, and Mason A. Porter, “Learning low-rank mesoscale structures of networks.”  Nature Communications 15, Article number: 224 (2024)  [Journal, Blog, Preprint, GitHub, Python package “ndlearn”] (Featured in Editor’s Highlights) 
  15. Joowon Lee, Hanbaek Lyu, and Weixin Yao, “Interpretable Feature Extraction by Supervised Dictionary Learning for Identification of Cancer-Associated Gene Clusters.” ICML Workshop on Computational Biology 2023 [paper, SDL_poster]
  16. Dohyun Kwon and Hanbaek Lyu, “Complexity of block coordinate descent with proximal regularization and applications to Wasserstein CP-dictionary learning.” ICML 2023 [Paper], 
  17. Ahmet Alacaoglu and Hanbaek Lyu, “Convergence of first-order methods for nonconvex constrained optimization with dependent data.” ICML 2023 [Paper,  PSGD_poster]
  18. Hanbaek Lyu, Facundo Memoli, and David Sivakoff, “Sampling random graph homomorphisms and applications to network data analysis.”  Journal of Machine Learning Research 24(9):1−79, 2023  [Journal, Preprint, GitHub]
  19. Hanbaek Lyu, Christopher Strohmeier, and Deanna Needell, “Online Nonnegative CP-dictionary Learning for Markovian Data” Journal of Machine Learning Research 23(148):1−50, 2022  [Journal, Preprint, GitHub]
  20. Hanbaek Lyu, Deanna Needell, and Laura Balzano, “Online matrix factorization for markovian data and applications to network dictionary learning.” Journal of Machine Learning Research. 21(251):1−49, 2020 [Journal, Preprint, GitHub] 
  21. Christopher Strohmeier, Hanbaek Lyu, and Deanna Needell, “Online nonnegative CP tensor decomposition for Markovian data” NeurIPS Workshop on Optimization for Machine Learning, 2020 [Publication,  Poster]
  22. Hanbaek Lyu, Georg Menz, Deanna Needell, and Christopher Strohmeier, “Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data.” 2020 Information Theory and Applications Workshop (ITA) 2020 (Publication, Preprint)                       ———————————————————————————–
  23. D. Duan and H. Lyu, “Regularized Overestimated Newton.”  Preprint (2025)
  24. David Clancy Jr., Hanbaek Lyu, and Sebastien Roch, “Likelihood landscape of binary latent model on a tree.” Preprint (2025)
  25. David Clancy Jr., Hanbaek Lyu, Sebastien Roch, Allan Sly, “Likelihood-Based Root State Reconstruction on a Tree: Sensitivity to Parameters and Applications.” Preprint (2025)
  26. Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu, “Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization”  Preprint (2023)
     

Cellular Automata and Interacting Particle Systems

  1. Sungwon Ahn, Matthew Junge, Hanbaek Lyu, Jacob Richey,  Lily Reeves, and David Sivakoff, “Diffusion-limited annihilating-coalescing systems.”
    Electron. J. Probab. 30: 1-20 (2025). DOI: 10.1214/25-EJP1286. [Journal] (2025)
  2. Kimberly Affeld, Christian Dean, Matthew Junge, Hanbaek Lyu, Connor Panish, Lily Reeves, “Four-parameter coalescing ballistic annihilation.” J Stat Phys 191, 89 (2024)[Journal, Preprint] (2024)
  3. Tobias Johnson, Matthew Junge, Hanbaek Lyu, and David Sivakoff, “Particle density in diffusion-limited annihilating systems.” Annals of Probability, Vol. 51, No. 6, 2301-2344. [Journal, Preprint] (2023)
  4. Luis Benitez, Matthew Junge, Hanbaek Lyu, Maximus Redman, Lily Reeves, “Three-velocity coalescing ballistic annihilation.” Electronic Journal of Probability, 28, 1-18 (2023) [Journal, Preprint]
  5. Matthew Junge and Hanbaek Lyu, “The phase structure in asymmetric ballistic annihilation.” Ann. Appl. Probab. 32(5): 3797-3816 (2022) (Journal, Preprint)
  6. Michael Damron, Hanbaek Lyu, David Sivakoff, “Stretched exponential decay for subcritical parking times on Z^d.”  Random Structures and Algorithms 2020 (Journal, Preprint) 
  7. Eric Foxall and Hanbaek Lyu, “Clustering in the three and four color cyclic particle systems in one dimension.” Journal of Statistical Physics, , Volume 171, Issue 3, pp 470–483. (Journal, Preprint)
  8. Hanbaek Lyu and David Sivakoff, “Persistence of sums of correlated increments and clustering in cellular automata.” Stochastic Processes and Applications, Volume 129, Issue 4, April 2019, Pages 1132-1152 (Journal, Preprint)
  9. Michael Damron, Janko Gravner, Matthew Junge, Hanbaek Lyu, and David Sivakoff, “Parking on transitive unimodular graphs.” Annals of Applied Probability, Volume 29, Number 4 (2019), 2089-2113 (Journal, Preprint)
  10. Janko Gravner, Hanbaek Lyu, and David Sivakoff, “Limiting behavior of 3-color excitable media on arbitrary graphs.” Annals of Applied Probability, Volume 28, Number 6 (2018), 3324-3357. (Journal, Preprint)                                                                                                                                

Coupled oscillators and Clock Synchronization

  1. Hanbaek Lyu, “Time complexity of Synchronization of discrete pulse-coupled oscillators on trees.” To appear in Journal of Cellular Automata. Preprint (2023)
  2. (From REU 2020) Hardeep Bassi*, Richard Yim*, Rohith Kodukula*, Joshua Vendrow*, Cherlin Zhu*, Hanbaek Lyu, “Learning to predict synchronization of coupled oscillators on randomly generated graphs.” Scientific Reports 12, Article number: 15056 (2022) [Journal, GitHub]
  3. Hanbaek Lyu, “Global synchronization of pulse-coupled oscillators on trees.” SIAM Journal on Applied Dynamical Systems 2018, Vol. 17, No. 2. (Journal, Preprint)
  4. Hanbaek Lyu, “Synchronization of finite-state pulse-coupled oscillators”, Physica D: Nonlinear Phenomena 303 (2015): 28-38. (Journal, Preprint)                                                                                                            ———————————————————————————– 
  5. (From REU 2022) Agam Goyal, Zhaoxing Wu, Richard P. Yim, Binhao Chen, Zihong Xu, and Hanbaek Lyu, “A latent linear model for nonlinear coupled oscillators on graphs.”  Preprint (2023)
  6. Ander Aguirre , Hanbaek Lyu, and David Sivakoff, “Phase transition in one-dimensional excitable media with variable
     interaction range” Preprint (2024)

Graph Theory

  1. Hanbaek Lyu, “Chromatic number, induced cycles, and non-separating cycles.” Graphs and Combinatorics. 36, 1297–1310 (2020) (Journal, Preprint)

Papers from REU projects

  1. Y. Guo*, N. Hanoian*, Z. Lin*, N. Liskij*, H. Lyu, D. Needell, J. Qu*, H. Sojico*, Y. Wang*, Z. Xiong*, and Z. Zou*, “Topic-aware Chatbot Using Recurrent Neural Networks and Nonnegative Matrix Factorization.” Preprint (2019) [From Summer REU 2019] [GitHub]

In  preparation

  1. Hanqin Cai, Hanbaek Lyu, Deanna Needell, “Robust Online CP Dictionary Learning”

Undergraduate works

  1. Hanbaek Lyu, “A note on the graph characteristics and Hadwiger’s conjecture.” arXiv preprint arXiv:1203.3710 (2012)

(author*=undergraduate student)

Probability, combinatorics, and complex systems