Submitted Manuscripts and Preprints
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression, joint with Ricardo Baptista and Yangxinyu Xie, 2024. (arXiv)
Statistical Advantages of Oblique Randomized Decision Trees and Forests, 2024 (arXiv)
Published Articles
The Star Geometry of Critic-Based Regularizer Learning, joint with Oscar Leong and Yong Sheng Soh, NeurIPS 2024 (Link)
Optimal Regularization for a Data Source, joint with Oscar Leong, Yong Sheng Soh, and Venkat Chandrasekaran, Foundations of Computational Mathematics, 2025. (Link)
Minimax Rates for High-Dimensional Random Tessellation Forests, joint with Ngoc Tran. Journal of Machine Learning Research, 2024. (Link)
Spectrahedral Regression, joint with Venkat Chandrsekaran. SIAM Journal on Optimization, 2023. (Link)
Stochastic geometry to generalize the Mondrian Process, joint with Ngoc Tran. SIAM Journal on Mathematics of Data Science, 2022. (Link)
Facets of spherical random polytopes, joint with Gilles Bonnet. Mathematische Nachrichten, 2022. (Link)
Couplings for determinantal point processes and their reduced Palm distributions with a view to quantifying repulsiveness, joint with Jesper Møller. Journal of Applied Probability, 2021. (Link)
Thin-shell concentration for zero cells of stationary Poisson mosaics. Advances in Applied Mathematics, 2020. (Link)
The stochastic geometry of one bit compression, joint with François Baccelli. Electronic Journal of Probability, 2019. (Link)
Reach of Repulsion of Determinantal Point Processes in High Dimensions, joint with François Baccelli, 2018. Journal of Applied Probability. (Link)
End-to-End Optimization of High Throughput DNA Sequencing, joint with F. Baccelli, G. de Veciana, and H. Vikalo. Journal of Computational Biology, 2016. (Link)