Aaron Sonabend W, Nilanjana Laha, Ashwin N Ananthakrishnan, Tianxi Cai, and Rajarshi Mukherjee. Submitted. “Semi-Supervised Off Policy Reinforcement Learning”.
Nilanjana Laha, Aaron Sonabend W, Rajarshi Mukherjee, and Tianxi Cai. Submitted. “Finding the optimal dynamic treatment regime using smooth Fisher consistent surrogate loss”.
Georg Hahn, Sharon M. Lutz, Nilanjana Laha, and Christoph Lange. Submitted. “A framework to efficiently smooth L1 penalties for linear regression”.
Nilanjana Laha. Submitted. “Location estimation for symmetric log-concave densities”.
Nilanjana Laha, Nathan Huey, Brent Coull, and Rajarshi Mukherjee. Submitted. “On Statistical Inference with High Dimensional Sparse CCA”.
Nilanjana Laha, Zoe Moodie, Ying Huang, and Alex Luedtke. Forthcoming. “Improved inference for vaccine-induced immune responses via shape-constrained methods.” Electronic Journal of Statistics.
Rebekka Burkholz, Nilanjana Laha, Rajarshi Mukherjee, and Alkis Gotovos. 2022. “On the Existence of Universal Lottery Tickets.” In ICLR.
Nilanjana Laha and Rajarshi Mukherjee. 2022. “On Support Recovery with Sparse CCA: Information Theoretic and Computational Limits.” IEEE Transactions on Information Theory.
Nilanjana Laha. 2021. “Adaptive estimation in symmetric location model under log-concavity constraint.” Electronic Journal of Statistics, 15, 1, Pp. 2939--3014.
Nilanjana Laha, Zhen Miao, and Jon A. Wellner. 2021. “Bi-s*-concave distributions.” Journal of Statistical Planning and Inference, 215, Pp. 127-157.
Georg Hahn, Sharon M Lutz, Nilanjana Laha, Michael H. Cho, Edwin K Silverman, and Christoph Lange. 2021. “A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD).” Statistics and Computing, 31, 3, Pp. 1-11.
Nilanjana Laha. 2019. “Estimation and testing under shape constraints.” University of Washington (PhD Thesis).