Trambak Banerjee

Trambak Banerjee

Assistant Professor at University of Kansas, School of Business

Working papers

  1. Harnessing The Collective Wisdom: Fusion Learning Using Decision Sequences From Diverse Sources.
    Banerjee T, Gang B and He J.
  2. Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity.
    Gang B and Banerjee T.
    Reproducibility: R code
  3. Nonparametric Empirical Bayes Prediction in Mixed Models.
    Banerjee T* and Sharma P.
  4. Nonparametric Empirical Bayes Estimation on Heterogeneous Data.
    Banerjee T, Fu L, Mukherjee G, James G and Sun W.
  5. Do financial regulators act in the public's interest? A Bayesian latent class estimation framework for assessing regulatory responses to banking crises.
    Sharma P and Banerjee T.
  6. Risk-Shifting, Regulation, and Government Assistance.
    Sharma P* and Banerjee T.
    *2023 NBER-NSF Seminar on Bayesian Inference in Econometrics and Statistics.

Publications

  1. Bootstrapped Edge Count Tests for Consistent Nonparametric Two-Sample Testing Under Heterogeneity.
    Banerjee T, Bhattacharya B and Mukherjee G. forthcoming: Journal of Computational and Graphical Statistics.
  2. Joint Modeling of Playing Time and Purchase Propensity in Massively Multiplayer Online Role Playing Games Using Crossed Random Effects.
    Banerjee T, Liu P, Mukherjee G, Dutta S and Che H. Annals of Applied Statistics (2023), Volume 17, no. 3, Pages 2533-2554.
  3. Rethinking gradient sparsification as total error minimization.
    Atal Narayan Sahu, Aritra Dutta, Ahmed M. Abdelmoniem, Trambak Banerjee, Marco Canini and Panos Kalnis. NeurIPS (2021).
  4. Improved Shrinkage Prediction under a Spiked Covariance Structure.
    Banerjee T, Mukherjee G and Paul D. Journal of Machine Learning Research (2021) 22(180):1−40.
    R-package: casp
  5. A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family.
    Banerjee T, Liu Q, Mukherjee G and Sun W. Journal of Machine Learning Research (2021) 22(67):1−46.
  6. A Nearest-Neighbor Based Nonparametric Test for Viral Remodeling in Heterogeneous Single-Cell Proteomic Data.
    Banerjee T, Bhattacharya B and Mukherjee G. Annals of Applied Statistics (2020), Volume 14, no. 4, Pages 1777-1805.
    R-package: truh
  7. A Large-scale Constrained Joint Modeling Approach For Predicting User Activity, Engagement And Churn With Application To Freemium Mobile Games.
    Banerjee T*, Mukherjee G, Dutta S and Ghosh P. Journal of the American Statistical Association (2020), Volume 115, no. 530, Pages 538-554. MATLAB-toolbox: cezij
    *Best Paper award: 5th International Conference on Business Analytics and Intelligence, 2017 at Indian Institute of Management, Bangalore.
  8. Adaptive Sparse Estimation with Side Information.
    Banerjee T*, Mukherjee G and Sun W. Journal of the American Statistical Association (2020), Volume 115, no. 532, Pages 2053-2067.
    R-package: asus
    *Distinguished Student Paper Award: 2019 ENAR Spring meeting.
    *Runner-up: 2017 IISA annual conference student poster competition.
  9. Invited Discussion of CARS: covariate assisted ranking and screening for large-scale two-sample inference by Cai, Sun and Wang.
    Banerjee T and Mukherjee G. Journal of the Royal Statistical Society, Series B (2019), Volume 81, Pages 223-224.
  10. Feature Screening in Large Scale Cluster Analysis.
    Banerjee T, Mukherjee G and Radchenko P. Journal of Multivariate Analysis (2017), Volume 161, Pages 191-212.
    R-package: fusionclust
  11. Mass Cytometric Analysis of HIV Entry, Replication, and Remodeling in Tissue CD4+ T Cells.
    Cell Reports (2017), Volume 20, Issue 4, 984 - 998.