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arXiv:2602.13781v1 Announce Type: cross Abstract: Let $D=(V(D),A(D))$ be a digraph with a terminal vertex subset $S\subseteq V(D)$ such that $|S|=k\geq 2$. An out-tree $T$ of...
arXiv:2602.13847v1 Announce Type: cross Abstract: We introduce a flexible framework based on response theory and score matching to suppress spurious, noncausal dependencies in reduced-order neural...
arXiv:2602.13863v1 Announce Type: cross Abstract: This paper presents the history of the online simulation program Java-DSP (J-DSP) and the most recent function development and deployment....
arXiv:2602.13871v1 Announce Type: cross Abstract: We formulate Ensemble-Conditional Gaussian Processes (Ens-CGP), a finite-dimensional synthesis that centers ensemble-based inference on the conditional Gaussian law. Conditional Gaussian...
arXiv:2602.13894v1 Announce Type: cross Abstract: Among two-candidate elections that treat the candidates symmetrically and never result in a tie, which voting rules are fair? A...
arXiv:2602.13906v1 Announce Type: cross Abstract: Stochastic approximation (SA) is a method for finding the root of an operator perturbed by noise. There is a rich...
arXiv:2602.13942v1 Announce Type: cross Abstract: In the era of large language models (LLMs), fine-tuning pretrained models has become ubiquitous. Yet the theoretical underpinning remains an...
arXiv:2602.13955v1 Announce Type: cross Abstract: Rydberg atomic receivers hold extremely high sensitivity to electric fields, yet their effective 3-dB baseband bandwidth under conventional electromagnetically induced...
arXiv:2602.14020v1 Announce Type: cross Abstract: We study operator-norm covariance estimation from heavy-tailed samples that may include a small fraction of arbitrary outliers. A simple and...
arXiv:2602.14029v1 Announce Type: cross Abstract: Iterative self-training (self-distillation) repeatedly refits a model on pseudo-labels generated by its own predictions. We study this procedure in overparameterized...
arXiv:2602.14053v1 Announce Type: cross Abstract: This paper establishes the mean-square convergence of a new stochastic, parameterized leapfrog scheme introduced in our companion paper Mazumder et...
arXiv:2602.14061v1 Announce Type: cross Abstract: This article introduces the Modified Parameterized Leapfrog Hamiltonian Monte Carlo (MPL-HMC) method, a novel extension of HMC addressing key limitations...
arXiv:2602.14063v1 Announce Type: cross Abstract: Extra-large apertures, high carrier frequencies, and integrated sensing and communications (ISAC) are pushing array processing into the Fresnel region, where...
arXiv:2602.14179v1 Announce Type: cross Abstract: The notion of word-representable graphs is a generalization of comparability graphs, in which graphs are represented by words. The complexity...
arXiv:2602.14199v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful approach for novel view synthesis. However, the number of Gaussian primitives...
arXiv:2602.14244v1 Announce Type: cross Abstract: Federated Learning provides a privacy-preserving paradigm for distributed learning, but suffers from statistical heterogeneity across clients. Personalized Federated Learning (PFL)...
arXiv:2602.14280v1 Announce Type: cross Abstract: We study optimization for losses that admit a variance-mean scale-mixture representation. Under this representation, each EM iteration is a weighted...
arXiv:2602.14284v1 Announce Type: cross Abstract: Data science is an integrated workflow of technical, analytical, communication, and ethical skills, but current AI benchmarks focus mostly on...
arXiv:2602.14315v1 Announce Type: cross Abstract: Metal objects pose a significant challenge in cone-beam computed tomography, as their strong and energy-dependent X-ray attenuation leads to inconsistent...
arXiv:2602.14342v1 Announce Type: cross Abstract: We show that high-accuracy guarantees for log-concave sampling -- that is, iteration and query complexities which scale as $\mathrm{poly}\log(1/\delta)$, where...
arXiv:2602.14379v1 Announce Type: cross Abstract: The local Hamiltonian (LH) problem is the canonical $\mathsf{QMA}$-complete problem introduced by Kitaev. In this paper, we show its hardness...
arXiv:2602.14384v1 Announce Type: cross Abstract: The rapid advancement of artificial intelligence in materials science requires data standards and data management practices that can capture the...
arXiv:2602.14415v1 Announce Type: cross Abstract: This paper investigates the problem of high-precision target localization in integrated sensing and communication (ISAC) systems, where the target is...
arXiv:2602.14440v1 Announce Type: cross Abstract: Standard regression methods typically optimize a single pointwise objective, such as mean squared error, which conflates the learning of ordering...