Publications

Preprints

1. Wensha Zhang, Toby Kenney, Lam Si Tung Ho. Evolutionary shift detection with ensemble variable selection. arXiv 

Published

1. Quan Huu Do, Binh T Nguyen, Lam Si Tung Ho. A Generalization Bound of Deep Neural Networks for Dependent Data. Statistics and Probability Letters 208: 110060. arXiv 

2. Wensha Zhang, Lam Si Tung Ho, Toby Kenney (2024). Detection of evolutionary shifts in variance under an Ornsten-Uhlenbeck model. BMC Ecology and Evolution 24, 11.  arXiv 

3. Esha Saha, Lam Si Tung Ho, Giang Tran (2023). SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics. Bulletin of Mathematical Biology 85:71. arXiv 

4. Lam Si Tung Ho*, Nicholas Richardson*, Giang Tran* (2023). Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data. Sampling Theory, Signal Processing, and Data Analysis 21:28.arXiv (*Authors are in alphabetical order)

5. Cuong N. Nguyen, Phong Tran, Lam Si Tung Ho, Vu C. Dinh, Anh Tuan Tran, Tal Hassner, Cuong V. Nguyen (2023). Simple Transferability Estimation for Regression Tasks. Conference on Uncertainty in Artificial Intelligence (UAI).

6. Nhat L Vu, Thanh P Nguyen, Binh T Nguyen, Vu Dinh, Lam Si Tung Ho (2023). When can we reconstruct the ancestral state? Beyond Brownian motion. Journal of Mathematical Biology 86, 88. arXiv 

7. Lam Si Tung Ho, Vu Dinh (2022). When can we reconstruct the ancestral state? A unified theory. Theoretical Population Biology 148: 22--27. arXiv 

8. Cuong N. Nguyen, Lam Si Tung Ho, Vu Dinh, Tal Hassner, Cuong V. Nguyen (2022). Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy. The International Symposium on Information Theory and Its Applications (ISITA). arXiv 

9. Gabriel Hassler, Max R. Tolkoff, William L. Allen, Lam Si Tung Ho, Philippe Lemey, Marc A. Suchard (2022). Inferring phenotypic trait evolution on large trees with many incomplete measurements. Journal of the American Statistical Association 117 (538): 678-692. arXiv

10. Estee Y. Cramer et al. (2022). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences 119 (15): e2113561119. medRxiv 

11. Estee Y. Cramer et al. (2022). The United States COVID-19 Forecast Hub dataset. Scientific Data 9: 462. medRxiv 

12. Lam Si Tung Ho, Edward Susko (2022). Ancestral state reconstruction with large numbers of sequences and edge-length estimation. Journal of Mathematical Biology 84, 21. arXiv

13. Lam Si Tung Ho*, Vu Dinh* (2022). Searching for Minimal Optimal Neural Networks. Statistics and Probability Letters 183: 109353. arXiv  (*Authors contributed equally)

14. Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu, Vu Dinh, Binh Nguyen (2022). Bayesian Pool-based Active Learning with Abstention Feedbacks. Neurocomputing 471: 242-250. arXiv

15. Paul Bastide, Lam Si Tung Ho, Guy Baele, Philippe Lemey, Marc A. Suchard (2021). Efficient Bayesian Inference of General Gaussian Models on Large Phylogenetic Trees. Annals of Applied Statistics 15 (2): 971-997. arXiv

16. Vu Dinh*,  Lam Si Tung Ho* (2021). Convergence of maximum likelihood supertree reconstruction. AIMS Mathematics 6 (8): 8870-8883. Invited, special issue of Mathematics in Science and Industry. (*Authors contributed equally)

17. Vu Dinh*, Lam Si Tung Ho* (2020). Consistent feature selection for analytic deep neural networks. Neural Information Processing Systems (NeurIPS). arXiv (*Authors contributed equally)

18. Lam Si Tung Ho*, Hayden Schaeffer*, Giang Tran*, Rachel Ward* (2020). Recovery guarantees for polynomial coefficients from weakly dependent data with outliers. Journal of Approximation Theory 259: 105472. arXiv (*Authors are in alphabetical order)

19. Lam Si Tung Ho, Binh T. Nguyen, Vu Dinh, Duy Nguyen (2020). Posterior concentration and fast convergence rates for generalized Bayesian learning. Information Sciences 538: 372-383. Mathematical Research Award (VIASM). arXiv

20. Lam Si Tung Ho*, Vu Dinh*, Frederick A Matsen IV, Marc A. Suchard (2020). On the convergence of the maximum likelihood estimator for the transition rate under a 2-state symmetric model. Journal of Mathematical Biology 80 (4): 1119-1138. arXiv (*Authors contributed equally)

21. Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho, Vu Dinh (2019). An active learning framework for set inversion. Knowledge-Based Systems 185: 104917. Invited paper 

22. Lam Si Tung Ho, Vu Dinh, Cuong V. Nguyen (2019). Multi-task learning improves ancestral state reconstruction. Theoretical Population Biology 126: 33-39. 

23. Lam Si Tung Ho, Forrest W. Crawford, Marc A. Suchard (2018). Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease. Annals of Applied Statistics 12 (3): 1993– 2021. arXiv

24. Vu Dinh*, Lam Si Tung Ho*, Marc A. Suchard, Frederick A Matsen IV (2018). Consistency and convergence rate of phylogenetic inference via regularization. Annals of Statistics 46 (4): 1481-1512. arXiv (*Authors contributed equally)

25. Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho, Vu Dinh (2018). OASIS: An Active Framework for Set Inversion. International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT). Granada, Spain. Best Paper Award. arXiv 

26. Forrest W. Crawford, Lam Si Tung Ho, Marc A. Suchard (2018). Computational methods for birth-death processes. WIREs Computational Statistics 10 (2): e1423.

27. Lam Si Tung Ho, Jason Xu, Forrest W. Crawford, Vladimir N. Minin, Marc A. Suchard (2018). Birth/birth-death processes and their computable transition probabilities with biological applications. Journal of Mathematical Biology 76 (4): 911-944. arXiv

28. Mandev S. Gill, Lam Si Tung Ho, Guy Baele, Philippe Lemey, Marc A. Suchard (2017). A Relaxed Directional Random Walk Model for Phylogenetic Trait Evolution. Systematic Biology 66 (3): 299-319. arXiv

29. Cécile Ané*, Lam Si Tung Ho*, Sebastien Roch* (2017). Phase transition on the convergence rate of parameter estimation under an Ornstein-Uhlenbeck diffusion on a tree. Journal of Mathematical Biology 74 (1): 355-385. arXiv (*Authors are in alphabetical order)

30. Vu Dinh, Lam Si Tung Ho, Binh T. Nguyen, Duy Nguyen (2016). Fast learning rates with heavy-tailed losses. Neural Information Processing Systems (NeurIPS). arXiv

31. David A. Baum, Cécile Ané, Bret Larget, Claudia Solís-Lemus, Lam Si Tung Ho, Peggy Boone, Chloe Drummond, Martin Bontrager, Steve Hunter, Bill Saucier (2016). Statistical evidence for common ancestry: Application to Primates. Evolution 70 (6): 1354-1363.

32. Daniel Irving Bernstein*, Lam Si Tung Ho*, Colby Long*, Mike Steel*, Katherine St. John*, Seth Sullivant* (2015). Bounds on the Expected Size of the Maximum Agreement Subtree. SIAM Journal on Discrete Mathematics 29 (4): 2065-2074. arXiv (*Authors are in alphabetical order)

33. Vu Dinh*, Lam Si Tung Ho*, Nguyen Viet Cuong, Duy Nguyen, Binh T. Nguyen (2015). Learning From Non-iid Data: Fast Rates for the One-vs-All Multiclass Plug-in Classifiers. Theory and Applications of Models of Computation (TAMC). arXiv (*Authors contributed equally)

34. Lam Si Tung Ho, Cécile Ané (2014). Intrinsic inference difficulties for trait evolution with Ornstein-Uhlenbeck models. Methods in Ecology and Evolution 5 (11): 1133-1146.

35. Lam Si Tung Ho, Cécile Ané (2014). A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Systematic Biology 63 (3): 397-408. Publisher's Award 2014

36. Tran Triet, Jeb Anthony Barzen, Sansanee Choowaew, Jon Mike Engels, Duong Van Ni, Nguyen Anh Mai, Khamla Inkhavilay, Kim Soben, Rath Sethik, Bhuvadol Gomontean, Le Xuan Thuyen, Aung Kyi, Nguyen Huy Du, Richard Nordheim, Lam Si Tung Ho, Dorn M. Moore, Scott Wilson (2014). Persistent Organic Pollutants in wetlands of the Mekong Basin. U.S. Geological Survey Scientific Investigations Report 2013-5196, 140 p.

37. Lam Si Tung Ho, Cécile Ané (2013). Asymptotic theory with hierarchical autocorrelation: Ornstein-Uhlenbeck tree models. Annals of Statistics 41 (2): 957-981. arXiv

38. Nguyen Viet Cuong, Lam Si Tung Ho, Vu Dinh (2013). Generalization and Robustness of Batched Weighted Average Algorithm with V-geometrically Ergodic Markov Data. International Conference on Algorithmic Learning Theory (ALT). arXiv

39. Nguyen Viet Cuong, Vu Dinh, Lam Si Tung Ho (2012). Mel-frequency Cepstral Coefficients for Eye Movement Identification. IEEE International Conference on Tools with Artificial Intelligence (ICTAI).

40. Duong Minh Duc*, Ho Si Tung Lam*, Nguyen Quang Thang*, Dinh Cao Duy Thien Vu* (2011). On Harnack's inequality for non-uniformly p-Laplacian equations. Acta Mathematica Vietnamica 36 (2): 199-214. (*Authors are in alphabetical order)

Unpublished works

1. Vu Dinh*, Lam Si Tung Ho*. Consistent feature selection for neural networks via Adaptive Group Lasso. arXiv (*Authors contributed equally)