Latest Research in Statistics Theory

Top Research Topics in Statistics Theory

• Optimization and Control — 25 papers
• Statistics Theory — 18 papers
• Machine Learning — 14 papers
• Machine Learning — 14 papers
• Numerical Analysis — 5 papers
• Computation — 5 papers
• Probability — 3 papers
• Stochastic processes and financial applications — 3 papers
• Benford’s Law and Fraud Detection — 3 papers
• Advanced NMR Techniques and Applications — 2 papers

Highest-Cited Papers

1. Local Asymptotic Normality for Mixed Fractional Brownian Motion with $0
2. Incremental Aggregation on the Grassmannian for Asynchronous Eigenspace Computation
3. Variational Bounds for Perceptron Learning from Structured Data
4. Stable Density Ridges: Consistency and Convergence of Subspace Constrained Mean Shift
5. Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles
6. Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability
7. Convergence analysis of controlled particle systems arising in deep learning: from finite to infinite sample size
8. Wedge Sampling: Efficient Tensor Completion with Nearly-Linear Sample Complexity
9. Oblivious Subspace Injection Is Not Enough for Relative Error
10. Pursuing Optimal Stepsize in Adaptive Gradient-Based Quadratic Optimization
11. Normalized First-Order Methods for Convex (L0, L1)-Smooth Optimization with Inexact Gradients
12. Adaptive Generalized Elliptical Slice Sampling
13. Wasserstein mixing time of the unadjusted Langevin algorithm
14. E8 Phased Hyper‑Spectral Embedding (E8‑PHSE) — E8 Intelligence Research
15. An Additional Characterization of the Triple Consisting of Normal, Gamma, and Inverse Gaussian Distributions
16. E8 Phased Hyper‑Spectral Embedding (E8‑PHSE) — E8 Intelligence Research
17. Closing the Gap: Efficient Algorithms for Discrete Wasserstein Barycenters
18. Gradient flows for empirical Bayes in high-dimensional linear models
19. Particle-based Generalised Stochastic Optimisation
20. At least seven modes in a heteroscedastic three-component bivariate Gaussian mixture