arXiv preprints from January 1, 2026 through September 11, 2026 — 04:44:14 EST
In electric drive modeling, identifying the magnetic flux maps is essential for predicting accurately the torque, parameterizing a controller for tracking the torque or creating a simulation model. However, the voltage output by the controller (commanded voltage) is usually disturbed by non-linearity of the inverter, which needs to be...
Synchronization often emerges spontaneously among interacting people, yielding practical benefits for tasks such as sports, physical rehabilitation, and collaborative manufacturing, and fostering a sense of unity and trust. Although visual interaction is typically considered the primary channel for achieving synchronization, it is...
Semantic communication systems such as deep semantic communication (DeepSC) offer high efficiency but are vulnerable to adversarial attacks on their underlying neural networks. We address a physical-layer man-in-the-middle (MitM) threat in which an adversary injects perturbations into the transmitted signal to distort its meaning. We...
Estimating causal effects of linguistic properties from observational text is difficult because the same document can contain both the treatment of interest and the non-treatment textual attributes needed for adjustment. Existing approaches often learn representations from the full text to capture latent confounding, but when...
Patient-reported pain location is diagnostically decisive for some presentations and nearly uninformative for others. The prevailing account treats this as a single gradient of diagnostic utility governed by anatomical complexity. That explanation conflates three epistemically distinct failures of localization, each with its own...
Combining electronic health record (EHR) data from multiple institutions is a valuable strategy for conducting post-market safety surveillance of medical products, but privacy concerns limit sharing individual-level data. We develop a novel federated learning (FL) method for multi-site post-market safety surveillance of medical...
Two central challenges in diffusion-based sampling are the theoretical one of understanding their remarkable effectiveness even in high-dimensional settings, and the practical one of designing algorithms with certified performance guarantees. We show that these questions are intimately connected via the \emph{denoising growth...
We consider a stochastic multi-objective bandit problem where, at each round, the agent selects a slate of $k$ arms and observes their $d$-dimensional reward vectors under semi-bandit feedback. We do not aim at identifying a single optimal arm; instead, we consider the problem of maintaining a small set of actions that jointly...
In modern Bayesian computation and parametric estimation, the marginal likelihood, serving as the denominator P(D) in Bayes' Theorem, is routinely bypassed via unnormalized proportionality relations. Even within specialized model-selection frameworks where it is explicitly evaluated to compute Bayes Factors, the denominator is treated...
In this paper, we derive a conditional copula representation for expectations of the form $\mathbb{E}[g(\boldsymbol{X})]$, where $\boldsymbol{X}$ is a random vector with arbitrary marginal distributions and $g$ is a measurable function satisfying suitable integrability conditions. The proposed representation explicitly separates the...
Religious radio is a widespread but understudied form of mass communication in the United States, and content-level analysis of it has been constrained by the absence of large-scale transcript data. This Data Descriptor presents a corpus of transcribed English-language religious radio broadcasts captured from live webstreams over a...
Regression estimates from observational data can depend on specification under multicollinearity, while sequential sums of squares (SS) depend on term order. We introduce Retrospective Orthogonal Design (ROD), which reconstructs conditional mean surfaces on a probability-balanced lattice. ROD preserves observed cell means, completes...
This article presents a statistical learning framework for studying the evolution of pediatric mental health-related emergency department (MHED) visit patterns across the pre-, during-, and post-COVID-19 pandemic periods using population-based administrative health records. The MHED records are formulated as zero-truncated recurrent...
The $k$-means++ algorithm is a standard and widely used seeding method for $k$-means clustering, but for a fixed number $k$ of centers its worst-case expected approximation ratio is $Θ(\log k)$. We consider the same algorithm when an adversary first fixes the dataset and some $K$; the number of centers $k$ is then chosen uniformly...
The Dirichlet process (DP) is the most common bayesian nonparametric prior, however, its properties as sampling distribution have not been studied nor inference on its parameters. Here we use the DP as a data generating model and make bayesian inference on its centering measure and precision parameter. We illustrate with a sequence of...
Meta-analyzing natural indirect effect estimates from multiple studies is increas- ingly used to synthesize evidence on causal pathways of interest. However, stan- dard mediation meta-analysis approaches are typically based on structural equation modeling, which fails to account for mediator-outcome confounding, is not read- ily...
This paper studies the convergence of stochastic gradient descent (SGD) when the implemented updates are subject to a persistent and state-dependent bias, in which the desired update is scaled by response functions component-wise. Our first contribution is to demonstrate that SGD in this setting implicitly optimizes a penalized...
In electromagnetic heating and other applications, we need to compute the volume enclosed by an isosurface of the 3D temperature distribution that is numerically represented on a rectangular grid. This situation arises naturally when the temperature distribution is obtained by solving a partial differential equation numerically using...
We consider the two-species particle system introduced by Stevens (2000) related to the doubly parabolic Keller-Segel equation. It consists of $N$ cells and of a varying number of chemoattractant particles. Cells diffuse in the plane and follow the (mollified) empirical gradient of concentration of chemoattractant. Chemoattractant...
For a finite subgroup $G\subset \operatorname{SL}(3,\mathbb{C})$, the Cautis--Logvinenko conjecture states that for each nontrivial irreducible representation $ρ$ of $G$, the image of the sheaf $\mathcal{O}_0\otimes ρ$ under the derived equivalence of Bridgeland--King--Reid is a pure sheaf on the $G$-Hilbert scheme. We prove this when...
We study the quasilinear Liouville equation \[ -Δ_n u=e^u \] on complete noncompact Riemannian manifolds with nonnegative Ricci curvature. Our first result shows that, if a solution $u$ satisfies the optimal logarithmic lower bound \[ u(x)\ge -\frac{n^2}{n-1}\log r(x)+o(\log r(x)) \quad \text{as }r(x)\to+\infty, \] then the underlying...
The Strong Szegő Limit Theorem is a theorem about the asymptotics of the determinants of large Toeplitz matrices. It can be reformulated as a probabilistic statement about eigenvalue statistics of random unitary matrices. We prove a multivariate generalization of the theorem in this latter form, replacing a single unitary with a...
For a ladder-system space $X_L$ with carrier $S\subseteq E^{ω_1}_ω$, the finite-label uniformization property $M_{<ω}$ characterizes countable metacompactness, and countable metacompactness is equivalent to the $Δ$-property. Both equivalences are known for stationary carriers. For arbitrary carriers, an active-tail formulation gives a...
We connect modal set theory with Boolean-valued models by developing an \emph{internal} Kripke semantics for modal formulas whose atomic propositions are set-theoretic sentences. Given a complete Boolean algebra $B$, we view its elements as ``local perspectives on truth'' inside the Boolean-valued universe $V^{(B)}$ and interpret the...
We have previously given a factorization of a symplectic column under the action of the parity involution which enabled to explicitly have written the inverse of the reduction map in the quantum Littlewood-Richardson bijection. Watanabe has written the reduction map as a composition of several maps, among them, combinatorial...