RG Li

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  • 2024 | Preprint
    ​ ​Multiscale Quantile Regression with Local Error Control​
    Liu, Z.& Li, H.​ (2024). DOI: https://doi.org/10.48550/ARXIV.2403.11356 
    ​Details  DOI  arXiv 
  • 2023 | Preprint
    ​ ​Adaptive minimax optimality in statistical inverse problems via SOLIT - Sharp Optimal Lepskii-Inspired Tuning​
    Li, H.& Werner, F.​ (2023). DOI: https://doi.org/10.48550/arxiv.2304.10356 
    ​Details  DOI  arXiv 
  • 2023 | Preprint
    ​ ​A scalable clustering algorithm to approximate graph cuts​
    Suchan, L.; Li, H.& Munk, A.​ (2023). DOI: https://doi.org/10.48550/ARXIV.2308.09613 
    ​Details  DOI 
  • 2022 | Journal Article
    ​ ​Seeded binary segmentation: a general methodology for fast and optimal changepoint detection​
    Kovács, S.; Bühlmann, P.; Li, H. & Munk, A.​ (2022) 
    Biometrika, art. asac052​.​ DOI: https://doi.org/10.1093/biomet/asac052 
    ​Details  DOI 
  • 2022 | Journal Article
    ​ ​A Variational View on Statistical Multiscale Estimation​
    Haltmeier, M.; Li, H.   & Munk, A. ​ (2022) 
    Annual Review of Statistics and Its Application, 9(1) pp. 343​-372​.​ DOI: https://doi.org/10.1146/annurev-statistics-040120-030531 
    ​Details  DOI 
  • 2021 | Journal Article
    ​ ​Frame-constrained total variation regularization for white noise regression​
    del Álamo, M.; Li, H.   & Munk, A. ​ (2021) 
    The Annals of Statistics, 49(3).​ DOI: https://doi.org/10.1214/20-AOS2001 
    ​Details  DOI  arXiv 
  • 2021 | Journal Article | Research Paper
    ​ ​Multiple haplotype reconstruction from allele frequency data​
    Pelizzola, M.; Behr, M.; Li, H. ; Munk, A.   & Futschik, A.​ (2021) 
    Nature computational science, 1(4) pp. 262​-271​.​ DOI: https://doi.org/10.1038/s43588-021-00056-5 
    ​Details  DOI 
  • 2020 | Preprint
    ​ ​Variational Multiscale Nonparametric Regression: Algorithms and Implementation​
    del Alamo, M.; Li, H. ; Munk, A.  & Werner, F.​ (2020)
    ​Details  arXiv 
  • 2020 | Preprint
    ​ ​Optimistic search strategy: Change point detection for large-scale data via adaptive logarithmic queries​
    Kovács, S.; Li, H. ; Haubner, L.; Munk, A.  & Bühlmann, P.​ (2020)
    ​Details  arXiv 
  • 2020 | Preprint
    ​ ​Seeded Binary Segmentation: A general methodology for fast and optimal change point detection​
    Kovács, S.; Li, H. ; Bühlmann, P.& Munk, A. ​ (2020)
    ​Details  arXiv 
  • 2020 | Preprint
    ​ ​Multiple Haplotype Reconstruction from Allele Frequency Data​
    Pelizzola, M.; Behr, M.; Li, H. ; Munk, A.  & Futschik, A.​ (2020). DOI: https://doi.org/10.1101/2020.07.09.191924 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper
    ​ ​Seeded intervals and noise level estimation in change point detection: a discussion of Fryzlewicz (2020)​
    Kovács, S.; Li, H.   & Bühlmann, P.​ (2020) 
    Journal of the Korean Statistical Society, 49(4) pp. 1081​-1089​.​ DOI: https://doi.org/10.1007/s42952-020-00077-2 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper
    ​ ​The essential histogram​
    Li, H. ; Munk, A. ; Sieling, H.   & Walther, G.​ (2020) 
    Biometrika, 107(2) pp. 347​-364​.​ DOI: https://doi.org/10.1093/biomet/asz081 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper | 
    ​ ​NETT: solving inverse problems with deep neural networks​
    Li, H. ; Schwab, J.; Antholzer, S. & Haltmeier, M.​ (2020) 
    Inverse Problems, 36(6) pp. 065005​.​ DOI: https://doi.org/10.1088/1361-6420/ab6d57 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper | 
    ​ ​Variational Multiscale Nonparametric Regression: Algorithms and Implementation​
    del Alamo, M.; Li, H. ; Munk, A.   & Werner, F. ​ (2020) 
    Algorithms, 13(11) pp. 296​.​ DOI: https://doi.org/10.3390/a13110296 
    ​Details  DOI 
  • 2019 | Journal Article | Research Paper | 
    ​ ​Multiscale Change-point Segmentation: Beyond Step Functions​
    Li, H. ; Guo, Q. & Munk, A. ​ (2019) 
    Electronic Journal of Statistics, 13(2) pp. 3254​-3296​.​ DOI: https://doi.org/10.1214/19-EJS1608 
    ​Details  DOI  arXiv 
  • 2018 | Preprint
    ​ ​Frame-constrained Total Variation Regularization for White Noise Regression​
    del Álamo, M.; Li, H.  & Munk, A. ​ (2018)
    ​Details  arXiv 
  • 2016 | Preprint
    ​ ​The Essential Histogram​
    Li, H. ; Munk, A. ; Sieling, H.  & Walther, G.​ (2016)
    ​Details  arXiv 

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