Research
Preprints and Submitted Articles:
- S. Chatterjee, P.S Dey and S. Goswami. Central Limit Theorem for Gram Schmidt Walk Design.
- S. Chatterjee and S. Sen. Regret Minimization in Isotonic, Heavy Tailed Contextual Bandits via Adaptive Confidence Bands.
- O.H.M Padilla and S. Chatterjee. Quantile Regression by Dyadic CART.
Publications:
- A. Chaudhuri and S. Chatterjee. A Cross Validation Framework for Signal Denoising with Applications to Trend Filtering, Dyadic CART and Beyond. Annals of Statistics. To appear.
- S. Chatterjee and S. Goswami. Spatially Adaptive Online Prediction of Piecewise Regular Functions. Algorithmic Learning Theory 2023, 35 pp., Proc. Mach. Learn. Res. (PMLR), 201.
- T.Zhang and S. Chatterjee. Element-wise Estimation Error of Generalized Fused Lasso. Bernoulli. To appear.
- Y.Yu, S. Chatterjee and H.Xu. Localizing Change Points in Piecewise Polynomials of General Degrees. To appear in Electronic Journal of Statistics.
- O.H.M Padilla and S. Chatterjee. Risk Bounds for Quantile Trend Filtering. Biometrika. To appear.
- S. Chatterjee and S. Goswami. Adaptive Estimation of Multivariate Piecewise Polynomials and Bounded Variation Functions by Optimal Decision Trees. Annals of Statistics. To appear.
- S. Chatterjee and S. Goswami. New Risk Bounds in 2D Total Variation Denoising. IEEE Transactions of Information Theory, 2021
- A. Guntuboyina, D. Lieu, S. Chatterjee and B. Sen. Spatial Adaptation in Trend Filtering. Annals of Statistics Vol. 48, p. 205 – 229, 2020.
- S. Chatterjee and S. Mukherjee. On Estimation in Tournaments and Graphs Under Monotonicity Constraints IEEE Transactions on Information Theory, Vol. 65, Issue: 6, 2019
- Q. Han, T. Wang, S. Chatterjee and R. Samworth. Isotonic Regression in General Dimensions. Annals of Statistics, Vol. 43, Number 5, p. 2440 – 2471, 2019. Here is a recorded talk about the above paper.
- S. Chatterjee and J. Lafferty. Adaptive Risk Bounds in Unimodal Regression, Bernoulli,
Vol. 25, Number 1, p. 1 – 25, 2019. - M. Bonakdarpour, S. Chatterjee, R. Barber, J. Lafferty. Prediction rule reshaping. 35th International Conference on Machine Learning (ICML 2018).
- S. Chatterjee and J. Lafferty. Denoising Flows on Trees. IEEE Transactions on Information Theory ( Volume: 64, Issue: 3, March 2018 )
- S. Chatterjee, A. Guntuboyina and B. Sen. Bernoulli. Bernoulli. On Matrix Estimation Under
Monotonicity Constraints, Vol. 24, p. 1072 – 1100, 2018. - Y. Zhu, S. Chatterjee, J. Duchi and J. Lafferty. Local minimax complexity of stochastic convex optimization. Advances in Neural Information Processing Systems (NeurIPS 2016), p. 3423 – 3431, 2016.
- S. Chatterjee. An Improved Global Risk Bound in Concave Regression. Electronic Journal of Statistics 10.1 (2016): 1608-1629
- 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, 2015
- S. Chatterjee and A. Barron. Information theoretic validity of Penalized Likelihood. IEEE International Symposium on Information Theory, ISIT 2014 (pp. 3027-3031).