Arnab Auddy
Mathematics · The Ohio State University
Publications
30
Citations
69
Est. group size
—
Recurring co-author estimate
Active years
9
Publishing since 2018
Arnab Auddy works in mathematical statistics, focusing on the theory behind analyzing large and complex datasets, such as those involving tensors (multi-dimensional arrays of numbers) and high-dimensional data with many variables. Recent work addresses statistical privacy (keeping individual data confidential while still learning from it), transfer learning (applying knowledge from one dataset to another), and methods for testing how reliable statistical estimates are. The work is largely theoretical, establishing mathematical guarantees and limits for these methods alongside some practical algorithms.
Publication output has grown steadily over the last decade, rising from occasional papers in 2017-2020 to a consistent 4-7 papers per year from 2023 to 2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
arXiv (Cornell University) · 2026
- Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
arXiv (Cornell University) · 2026
- Large-dimensional independent component analysis: Statistical optimality and computational tractability
The Annals of Statistics · 2025
- Minimax and adaptive transfer learning for nonparametric classification under distributed differential privacy constraints
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2025
- Transfer learning via Regularized Linear Discriminant Analysis
arXiv (Cornell University) · 2025
- Newfluence: Boosting Model interpretability and Understanding in High Dimensions
arXiv (Cornell University) · 2025
- Gaussian Certified Unlearning in High Dimensions: A Hypothesis Testing Approach
arXiv (Cornell University) · 2025
- On Spectral Learning for Odeco Tensors: Perturbation, Initialization, and Algorithms
arXiv (Cornell University) · 2025
- Certified Data Removal Under High-dimensional Settings
arXiv (Cornell University) · 2025
- Exact detection thresholds and minimax optimality of Chatterjee’s correlation coefficient
Bernoulli · 2024
- Tensors in High-Dimensional Data Analysis: Methodological Opportunities and Theoretical Challenges
Annual Review of Statistics and Its Application · 2024
- Approximate Leave-One-Out Cross Validation for Regression With ℓ₁ Regularizers
IEEE Transactions on Information Theory · 2024
- Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
arXiv (Cornell University) · 2024
- Tensor Methods in High Dimensional Data Analysis: Opportunities and Challenges
arXiv (Cornell University) · 2024
- Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
arXiv (Cornell University) · 2024
- arXiv (Cornell University)×19
- IEEE Transactions on Information Theory×2
- Bernoulli×1
- Annual Review of Statistics and Its Application×1
- Foundations of Computational Mathematics×1
- Will Wei Sun
Mathematics · Purdue University West Lafayette
- Qingsong Wang
Engineering · The Ohio State University
- Chen Chen
Mathematics · The Ohio State University
- Jordan Awan
Computer Science · Purdue University West Lafayette
- Zhanyu Wang
Mathematics · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
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