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Found 5 papers, 1 papers with code
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems
This paper develops a new dimension-free Azuma-Hoeffding type bound on summation norm of a martingale difference sequence with random individual bounds.
Online Bootstrap Inference with Nonconvex Stochastic Gradient Descent Estimator
Furthermore, our analysis yields an intermediate result: the in-expectation error convergence rate for the original SGD estimator in nonconvex settings, which is comparable to existing results for convex problems.
Fast parameter estimation of Generalized Extreme Value distribution using Neural Networks
The heavy-tailed behavior of the generalized extreme-value distribution makes it a popular choice for modeling extreme events such as floods, droughts, heatwaves, wildfires, etc.
Fitting Sparse Markov Models to Categorical Time Series Using Regularization
A more general approach is called Sparse Markov Model (SMM), where all possible histories of order $m$ form a partition so that the transition probability vectors are identical for the histories belonging to a particular group.
A Bootstrap-based Inference Framework for Testing Similarity of Paired Networks
We live in an interconnected world where network valued data arises in many domains, and, fittingly, statistical network analysis has emerged as an active area in the literature.
