The lack of stochastic convergence analysis

The gap

Evidence profile

Sourced from the stated research gap of the source papers, classified as general, spanning 2 journals.

Supporting evidence — 3 representative gaps

• Stochastic Convergence Analysis for Large-Scale Linear Discrete Ill-posed Problems (2026) · arXiv

  The lack of stochastic convergence analysis for large-scale linear discrete ill-posed problems with random noise. The need for an adaptive strategy suitable for large-scale computation.

  generalstated research gapevidence 5/5
  Keywords: lack stochastic convergence analysis large-scale linear discrete ill-posed
• Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation (2026) · arXiv

  The gap in existing literature is the lack of finite-sample Gaussian approximation guarantees for federated linear stochastic approximation. The gap in existing literature is the lack of a new analysis of the convergence of FedLSA with decreasing step size and increasing number of local iterations.

  generalstated research gapevidence 5/5
  Keywords: gap existing literature lack finite-sample gaussian approximation guarantees
• A Note on Piecewise Affine Decision Rules for Robust, Stochastic, and Data-Driven Optimization (2026) · Operations Research · doi

  The lack of efficient algorithms for multistage stochastic programs. The need for better approximation guarantees in stochastic settings. The limitation of existing frameworks to single-stage problems.

  generalstated research gapevidence 5/5
  Keywords: lack efficient algorithms multistage stochastic programs need better

Questions about this gap