Research

Research Interests

• Tensors

• Statistical and Computational Tradeoffs

• Spectral Methods in High Dimensional Statistics

• Nonparametric Independence Testing

Publications and Preprints

• Auddy, A., Cai, T. Tony and Chakraborty, A. (2024+)
  Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints.
  Submitted.

• Auddy, A., Xia, D. and Yuan, M. (2024+)
  Tensor Methods in High Dimensional Data Analysis: Opportunities and Challenges.
  Submitted.

• Auddy, A., Cai, T. Tony and Li, H. (2024+)
  Regressing Multivariate Gaussian Distribution on Vector Covariates for Co-expression Network Analysis.
  Submitted.

• Zou, H., Auddy, A., Rahnama Rad, K. and Maleki, A. (2024+)
  Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
  Submitted.

• Auddy, A., Zou, H., Rahnama Rad, K. and Maleki, A. (2023+)
  Approximate Leave-one-out Cross Validation for Regression with $\ell_1$ Regularizers
  IEEE Trans. Info. Theory, accepted. Shorter version accepted as oral presentation in AISTATS 2024.

• Arya S., Auddy, A. et al. (2023+)
  The Gromov-Wasserstein distance between spheres
  Found. Comput. Math., accepted.

• Auddy, A. and Yuan, M. (2023+)
  Large Dimensional Independent Component Analysis: Statistical Optimality and Computational Tractability
  Annals of Statistics, accepted.

• Auddy, A. and Yuan, M. (2021)
  On Estimating Rank-One Spiked Tensors in the Presence of Heavy Tailed Errors
  IEEE Trans. Info. Theory, 2022.

• Auddy, A. , Deb, N. and Nandy, S. (2021)
  Exact Detection Thresholds for Chatterjee’s Correlation
  Bernoulli, 2024.

• Bhattacharyya, R. et al.(2021)
  Role of Multi-resolution Vulnerability Indices in COVID-19 spread: A Case Study in India .
  BMJ Open, 2022.

• Auddy, A. and Yuan, M. (2020)
  Perturbation Bounds for (Nearly) Orthogonally Decomposable Tensors with Statistical Applications.
  Information and Inference: A Journal of the IMA, 2022.

• Khudabukhsh, W., Auddy, A., Disser, Y. and Koeppl, H. (2018)
  Approximate lumpability for Markovian agent-based models using local symmetries.
  Journal of Applied Probability, 2019.