11) O.H.M Padilla and S. Chatterjee. Risk Bounds for Quantile Trend Filtering. Biometrika. To appear. Available at https://arxiv.org/pdf/2007.07472.pdf.
10) S. Chatterjee and S. Goswami. Adaptive Estimation of Multivariate Piecewise Polynomials and Bounded Variation Functions by Optimal Decision Trees. Annals of Statistics. To appear. Available at https://arxiv.org/abs/1911.11562.
9) S. Chatterjee and S. Goswami. New Risk Bounds in 2D Total Variation Denoising. IEEE Transactions of Information Theory. DOI: 10.1109/TIT.2021.3059657. Available at https://arxiv.org/abs/1902.01215.
8) A. Guntuboyina, D. Lieu, S. Chatterjee and B. Sen. Adaptive risk bounds in univariate total variation denoising and trend filtering. Annals of Statistics, Vol 48, Pages 205-229. Available at https://arxiv.org/abs/1702.05113
7) S. Chatterjee and S. Mukherjee. On Estimation in Tournaments and Graphs Under Monotonicity Constraints.IEEE Transactions on Information Theory. DOI: 10.1109/TIT.2019.2893911 Available at https://arxiv.org/abs/1603.04556
Here is a recorded talk about the above paper.
5) S. Chatterjee and J. Lafferty. Denoising Flows on Trees. IEEE Transactions on Information Theory ( Volume: 64, Issue: 3, March 2018 ). DOI: 10.1109/TIT.2017.2782369. Available at https://arxiv.org/abs/1602.08048
3) S. Chatterjee. An Improved Global Risk Bound in Concave Regression. Electronic Journal of Statistics 10.1 (2016): 1608-1629. Available at https://arxiv.org/abs/1512.04658
1) S. Chatterjee, A. Guntuboyina, and B. Sen. On risk bounds in isotonic and other shape restricted regression problems. Annals of Statistics. vol. 43, pages 1774-1800. Available at https://arxiv.org/abs/1311.3765
Peer Reviewed Conference Papers:
3) M. Bonakdarpour, S. Chatterjee, R. Barber, J. Lafferty. 35th International Conference on Machine Learning (ICML 2018). Available at arXiv:1805.06439.
2) Y. Zhu, S. Chatterjee, J. Duchi and J. Lafferty. Local minimax complexity of stochastic convex optimization. Advances in Neural Information Processing Systems 29, 2016. Available at https://arxiv.org/abs/1605.07596
1) S. Chatterjee and A. Barron. Information theoretic validity of Penalized Likelihood. http://ieeexplore.ieee.org/document/6875390/ In 2014 IEEE International Symposium on Information Theory, ISIT 2014 (pp. 3027-3031). Available at https://arxiv.org/abs/1401.6714
Preprints/Under Preparation Articles
- S. Chatterjee and S. Sen. Regret Minimization in Isotonic, Heavy Tailed Contextual Bandits via Adaptive Confidence Bands.
- Y.Yu and S. Chatterjee. Localizing Change Points in Piecewise Polynomials of General Degrees. Available at https://arxiv.org/abs/2007.09910
- O.H.M Padilla and S. Chatterjee. Quantile Regression by Dyadic CART. Available at https://arxiv.org/abs/2110.08665