On the Statistical Optimality of Optimal Decision Trees

This paper establishes a comprehensive statistical theory for globally optimal empirical risk minimization decision trees by deriving sharp oracle inequalities and minimax optimal rates over a novel piecewise sparse heterogeneous anisotropic Besov space, thereby providing rigorous theoretical guarantees for their performance in high-dimensional regression and classification under both sub-Gaussian and heavy-tailed noise settings.

Zineng Xu, Subhroshekhar Ghosh, Yan Shuo Tan2026-03-06🔢 math

Integral Formulation and the Brézis-Ekeland-Nayroles-Type Principle for Prox-Regular Sweeping Processes

This paper establishes a unified bounded-variation solution framework for prox-regular sweeping processes by proving the equivalence between a new integral formulation with a quadratic correction term and the standard differential-measure formulation, while also deriving a Brézis-Ekeland-Nayroles-type variational characterization that ensures stability under uniform limits.

Juan Guillermo Garrido, Emilio Vilches2026-03-06🔢 math

Weighted Sobolev Inequalities via the Meyers--Ziemer Framework: Measures, Isoperimetric Inequalities, and Endpoint Estimates

This paper establishes a new global endpoint Sobolev inequality for measures that extends the Meyers-Ziemer theorem by incorporating a maximal function, thereby unifying and advancing the understanding of weighted bounded variation, isoperimetric inequalities, and fractional operator estimates while identifying sharp conditions for non-endpoint cases.

Simon Bortz, Kabe Moen, Andrea Olivo + 2 more2026-03-06🔢 math

Spatially-aware Secondary License Sharing in mmWave Networks

This paper proposes and analytically evaluates a spatially-aware secondary license sharing framework for mmWave networks that leverages the directional nature of signals and blockage conditions to optimize spectrum sharing, demonstrating that these physical characteristics can significantly enhance transmission opportunities for secondary users while maintaining primary network performance.

Shuchi Tripathi, Abhishek K. Gupta2026-03-06🔢 math

Thresholds for colouring the random Borsuk graph

This paper establishes that the chromatic number of the random Borsuk graph transitions from being kk-colourable to requiring more than kk colours when the average degree is constant for $2 \leq k \leq d,andfurtheridentifiessharpthresholdsforthesetransitions,particularlycharacterizingthe, and further identifies sharp thresholds for these transitions, particularly characterizing the k=2$ case via continuum AB percolation.

Álvaro Acitores Montero, Matthias Irlbeck, Tobias Müller + 1 more2026-03-06🔢 math

Thermodynamic Response Functions in Singular Bayesian Models

This paper establishes a unified thermodynamic response framework for singular Bayesian models, demonstrating that posterior tempering induces a hierarchy of observables that naturally interpret complex learning-theoretic quantities like the real log canonical threshold and WAIC as free-energy derivatives, thereby revealing phase-transition-like structural reorganizations in models such as neural networks and Gaussian mixtures.

Sean Plummer2026-03-06🔢 math