6 citations · 7 across the 11 of their papers we have counts for
12 papers
On a Class of Block-Regularized Preconditioned Iterative Methods for Indefinite Least-Squares Problems
Pinki Khatun
This paper proposes a novel block-regularized splitting (BRS) framework for the efficient solution of indefinite least-squares (ILS) problems. Based on a block-wise regularization…
Do Existing Preconditioners Improve Biomedical Tabular Foundation Learning? An Empirical Study on TabPFN Optimization
M. Sajid, Pinki Khatun, M. Tanveer
Tabular foundation models have recently shown strong potential for structured biomedical data analysis. Among them, TabPFN has emerged as an effective approach for low-data tabular…
Physics-Informed Broad Learning System: An Efficient Backpropagation-Free Framework for Solving Partial Differential Equations
Pinki Khatun, M. Sajid, Abhinav Jha +1
Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs) by embedding governing physical laws into deep neural…
Diophantine Equation over number fields
Pinki Khatun
Let , where is a positive square-free integer, and denote by the ring of integers of $…
Structured Backward Errors of Sparse Generalized Saddle Point Problems with Hermitian Block Matrices
Sk. Safique Ahmad, Pinki Khatun
In this paper, we derive the structured backward error (BE) for a class of generalized saddle point problems (GSPP) by preserving the sparsity pattern and Hermitian structures of t…
Partial Condition Numbers for Double Saddle Point Problems
Sk. Safique Ahmad, Pinki Khatun
This paper presents a unified framework for investigating the partial condition number (CN) of the solution of double saddle point problems (DSPPs) and provides closed-form express…
Sparsity-Preserving Structured Backward Error Analysis for Double Saddle Point Problems
Pinki Khatun, Sk. Safique Ahmad
Backward error (BE) analysis emerges as a powerful tool for assessing the backward stability and strong backward stability of numerical algorithms. In this paper, we explore struct…
A Class of Generalized Shift-Splitting Preconditioners for Double Saddle Point Problems
Sk. Safique Ahmad, Pinki Khatun
In this paper, we propose a generalized shift-splitting (GSS) preconditioner, along with its two relaxed variants to solve the double saddle point problem (DSPP). The convergence o…
Structured Backward Errors for Special Classes of Saddle Point Problems with Applications
Sk. Safique Ahmad, Pinki Khatun
In the realm of numerical analysis, the study of structured backward errors (BEs) in saddle point problems (SPPs) has shown promising potential for development. However, these inve…
A robust parameterized enhanced shift-splitting preconditioner for three-by-three block saddle point problems
Sk. Safique Ahmad, Pinki Khatun
This paper proposes a new parameterized enhanced shift-splitting (PESS) preconditioner to solve the three-by-three block saddle point problem (SPP). Additionally, we introduce a lo…
Condition numbers for the Moore-Penrose inverse and the least squares problem involving rank-structured matrices
Sk. Safique Ahmad, Pinki Khatun
Perturbation theory plays a crucial role in sensitivity analysis, which is extensively used to assess the robustness of numerical techniques. To quantify the relative sensitivity o…
Structured condition numbers for a linear function of the solution of the generalized saddle point problem
Sk. Safique Ahmad, Pinki Khatun
This paper addresses structured normwise, mixed, and componentwise condition numbers (CNs) for a linear function of the solution to the generalized saddle point problem (GSPP). We…