collaborators

7 papers

cs.DS2026

Contextual Fraction on Permutation Gain Graphs: Exact Algorithms, Query Lower Bounds, and Dynamic Maintenance

Ronald Katende

For an explicitly represented finite empirical model, deciding whether the contextual fraction is strictly below one is NP-complete, while the standard exact linear program has one…

cs.LG2026

Counterfactual Operator Relevance for PDE Discovery: Screening, Pruning, and Identifiability

Ronald Katende

We study operator relevance in data-driven partial differential equation (PDE) discovery. Sparse residual methods can select terms that improve residual fit, but residual contribut…

cs.LG2026

Geometry as a Missing Axis of Representation Quality: The Variational Geometric Information Bottleneck under Data Scarcity

Ronald Katende

We study latent geometry as an explicit component of representation quality in data-scarce learning. For an encoder (ϕ), we define (Q_{β,γ}(ϕ)=I(ϕ(X);Y)-β\mathcal C(ϕ)-γd_{…

math.NA2026

Core-Conditioned Regularized Matrix Tri-Factorization for High-Dimensional Structured Systems

Ronald Katende

This paper studies a regularized matrix tri-factorization \(A\approx PDQ\), where \(P\) and \(Q\) are side factors and \(D\) is a central core whose conditioning can be explicitly…

cs.LG2025

Interpretive Efficiency: Information-Geometric Foundations of Data Usefulness

Ronald Katende

Interpretability is central to trustworthy machine learning, yet existing metrics rarely quantify how effectively data support an interpretive representation. We propose Interpreti…

math.NA2025

Structured Variational -Decomposition for Accurate and Stable Low-Rank Approximation

Ronald Katende

We introduce the -decomposition, a non-orthogonal matrix factorization of the form , where , , and…