Tootfinder

Crosslisted article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Stable convergence of partial sum processes towards discontinuous limits
Johannes Brutsche
https://arxiv.org/abs/2608.12740 https://mastoxiv.page/@arXiv_mathPR_bot/117092840163122403
- Bayesian Inference Procedures for A/B Testing: An Overview
M{\aa}rten Schultzberg, Mattias Fr{\aa}nberg
https://arxiv.org/abs/2608.12949 https://mastoxiv.page/@arXiv_statME_bot/117092799825341949
- Estimation of distribution functions, their jumps and interval probabilities under measurement error
Kairat Mynbaev, Carlos Martins-Filho, Chad Brown
https://arxiv.org/abs/2608.13152 https://mastoxiv.page/@arXiv_econEM_bot/117092724945077876
- Extreme principal minors of Wishart and deformed GOE matrices
Zhanrui Dong, Tiefeng Jiang, Tuan Pham, Jianfeng Yao
https://arxiv.org/abs/2608.13154 https://mastoxiv.page/@arXiv_mathPR_bot/117092881421641444
- Sinkhorn Linearization and the Spectral Proxy: Unifying the Statistical and Algorithmic Theory of...
Han Dong, Jiaming Li, Yongqiang Gong, Ruixi Li, Yin Liu
https://arxiv.org/abs/2608.13201 https://mastoxiv.page/@arXiv_statML_bot/117092803789923153
- Weighted cumulative past inaccuracy and Kullback-Leibler divergence based on extropy: properties,...
Bighneswar Sahoo, Suchandan Kayal
https://arxiv.org/abs/2608.13363 https://mastoxiv.page/@arXiv_statME_bot/117092858417590746
- Nearly sharp comparison results for sliced and max-sliced Wasserstein distances
Jonathan Niles-Weed, Jacob Shkrob
https://arxiv.org/abs/2608.13374 https://mastoxiv.page/@arXiv_mathPR_bot/117092901477246948
- Theoretical Properties of Covariate-Adaptive Randomization with a Diverging Number of Covariates
Yuhang Tao, Li-Xin Zhang
https://arxiv.org/abs/2608.13442 https://mastoxiv.page/@arXiv_statME_bot/117092865494823071
- The data geometry of masking diffusion: Certified-optimal schedules via unmasking growth complexity
Martin J. Wainwright
https://arxiv.org/abs/2608.13520 https://mastoxiv.page/@arXiv_csLG_bot/117092942960850473
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Crosslisted article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Graphical Models for Multivariate Count Data
Iza Danielewska, Bartosz Ko{\l}odziejek
https://arxiv.org/abs/2608.11366 https://mastoxiv.page/@arXiv_statME_bot/117087137518300934
- Semiparametric efficient estimation of the Cox regression coefficient when there can be ties
Benjamin R Baer
https://arxiv.org/abs/2608.11399 https://mastoxiv.page/@arXiv_statME_bot/117087137911796087
- Kernel Methods for Learning Operators with Multiple Inputs and Outputs
Adrien Weihs, Chunyang Liao, Jingmin Sun, Hayden Schaeffer
https://arxiv.org/abs/2608.11831 https://mastoxiv.page/@arXiv_csLG_bot/117087254700651171
- Efficient Response-Adaptive Randomization for Multi-arm Trials with Prioritized Composite Endpoints
Ayon Mukherjee
https://arxiv.org/abs/2608.11953 https://mastoxiv.page/@arXiv_statME_bot/117087188083583909
- Deviation inequalities for U-processes of growing order, with applications to half-space depth
Stanislav Minsker, Shunan Yao
https://arxiv.org/abs/2608.12056 https://mastoxiv.page/@arXiv_mathPR_bot/117087117268165539
- Sharp Berry-Esseen Bounds for the Log Determinant of a Gaussian Sample Correlation Matrix
Hongru Zhao
https://arxiv.org/abs/2608.12242 https://mastoxiv.page/@arXiv_mathPR_bot/117087153642598120
- A contiguity approach to replica symmetric marginals
Ernesto Mordecki, Anas A. Rahman, Manuel S\'aenz
https://arxiv.org/abs/2608.12309 https://mastoxiv.page/@arXiv_mathph_bot/117087180577891013
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Replaced article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[2/3]:
- Multicritical points of gravitational solitons and a black hole in four dimensions
Moaathe Belhaj Ahmed, Mois\'es Bravo-Gaete, Robert B. Mann, Constanza Quijada
https://arxiv.org/abs/2605.24783 https://mastoxiv.page/@arXiv_hepth_bot/116639897763402557
- Brane flows
Georgios Papadopoulos, Kostas Skenderis
https://arxiv.org/abs/2605.31181 https://mastoxiv.page/@arXiv_hepth_bot/116673829986872182
- Weyl conformal geometry vs Riemannian geometry of Weyl gauge invariant (dressed) metric
D. M. Ghilencea, V. -M. Mandric
https://arxiv.org/abs/2606.08080 https://mastoxiv.page/@arXiv_hepth_bot/116719153397467346
- Free-Field Construction of Heterotic String Compactified on Calabi-Yau Orbifolds via Corresponden...
Alexander Belavin, Doron Gepner, Grigory Makarov
https://arxiv.org/abs/2606.27490 https://mastoxiv.page/@arXiv_hepth_bot/116832327091097035
- Exact Planar Black Hole in AdS-Einstein-Scalar Gravity with IR-Emergent Nearly Conformal Fluid
Sangheon Yun
https://arxiv.org/abs/2606.31901 https://mastoxiv.page/@arXiv_hepth_bot/116843780286505261
- AdS Black Holes Are Short-Lived inside the Spectral Form Factor
Jos\'e L. F. Barb\'on, Eduardo Velasco-Aja
https://arxiv.org/abs/2607.21704
- Generalized comodule tube algebras for boundary and domain wall defects of (2 1)D topological order
Zhian Jia, Sheng Tan
https://arxiv.org/abs/2608.05071 https://mastoxiv.page/@arXiv_hepth_bot/117047570919781079
- Surviving correlations across a horizon: reflected entropy for bosonic fields in non-inertial fra...
Sayid Mondal
https://arxiv.org/abs/2608.05473 https://mastoxiv.page/@arXiv_hepth_bot/117053235449252443
- Cluster algebras and tilings for the m=4 amplituhedron
Even-Zohar, Lakrec, Parisi, Tessler, Sherman-Bennett, Williams
https://arxiv.org/abs/2310.17727 https://mastoxiv.page/@arXiv_mathCO_bot/111322217178993182
- Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems
Ori Shem-Ur, Khen Cohen, Aviv Orly, Yaron Oz
https://arxiv.org/abs/2401.04013
- Gravity and the Hierarchy Problem
Thede de Boer, Jisuke Kubo, Manfred Lindner, Markus Reinig
https://arxiv.org/abs/2510.12882 https://mastoxiv.page/@arXiv_hepph_bot/115382945122925880
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Why #CodeQuality Still Matters in the Age of #AI Agents
https://medium.com/@ramtop/why-…

Community Matters
Join Nicky as she catches up with community leaders to hear inspiring stories, expert insights, and actionable ideas to create positive change...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/community-matters/

I submit that a moving melodic bassline is a most underrated musical device. And this band, the Lucksmiths, are the antidote. Consider https://thelucksmiths.bandcamp.com/track/motorscooter (and everything else in their catalogue)...

I love the #atop tool (https://www.atoptool.nl/) to monitor system metrics. Optionally it comes with a background process to collect the metrics for the past 30 days locally. You can use atopsar to analyze the last 30 days. I h…

Crosslisted article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[1/2]:
- Living on the Edge of Effective Field Theory: Near-Extremal Black Holes in Quadratic Gravity
Kelvin Ka-Ho Lam, Gary T. Horowitz, Nicol\'as Yunes
https://arxiv.org/abs/2608.05268 https://mastoxiv.page/@arXiv_grqc_bot/117053119278147418
- Relative entropy of entanglement of Haar random states
Takato Mori, Beni Yoshida
https://arxiv.org/abs/2608.05274 https://mastoxiv.page/@arXiv_quantph_bot/117053252355717367
- Theory of Measurement-Altered Criticality
Kabir Khanna, Sara Murciano, Romain Vasseur
https://arxiv.org/abs/2608.05289 https://mastoxiv.page/@arXiv_condmatstatmech_bot/117053093687616139
- Self-dual $S_3$ gauge theory in 2 1d: lattice model and topological phase transitions
Da-Chuan Lu, Chong Wang, Ashvin Vishwanath
https://arxiv.org/abs/2608.05294 https://mastoxiv.page/@arXiv_condmatstrel_bot/117053135203168433
- 3-form dark energy and cosmic birefringence
Kohei Kamada, Tucker Manton
https://arxiv.org/abs/2608.05296 https://mastoxiv.page/@arXiv_astrophCO_bot/117053109615577309
- GOOFy-compatible 3HDMs and beyond
I. de Medeiros Varzielas, A. Kun\v{c}inas
https://arxiv.org/abs/2608.05304 https://mastoxiv.page/@arXiv_hepph_bot/117053194550154760
- Beyond Borel Windows: A Systematic Optimization Framework for QCD Sum Rules
Raphael M. Albuquerque
https://arxiv.org/abs/2608.05322 https://mastoxiv.page/@arXiv_hepph_bot/117053194943710217
- Quantum information loss
James Fullwood, Wu-zhong Guo, Boyu Yang
https://arxiv.org/abs/2608.05535 https://mastoxiv.page/@arXiv_quantph_bot/117053277916138502
- Coherent and Stochastic Axion Dark Matter from Thermal Relaxation
Gurmani, Cilli, Channuie, Abdujabbarov, Atamurotov, G\"udekli
https://arxiv.org/abs/2608.05538 https://mastoxiv.page/@arXiv_hepph_bot/117053223846614186
- Asymmetric Quantum Oppenheimer-Snyder Collapse
Micha{\l} Bobula, Tomasz Paw{\l}owski
https://arxiv.org/abs/2608.05818 https://mastoxiv.page/@arXiv_grqc_bot/117053193567517392
- Triviality in a Non-Perturbative Second-Order Mean-Field Theory for $\phi^4_4$
Majdouline Borji
https://arxiv.org/abs/2608.05998 https://mastoxiv.page/@arXiv_mathph_bot/117053148149785707
- Measurement-induced entanglement Hamiltonian
Viktor Eisler, Erik Tonni
https://arxiv.org/abs/2608.06006 https://mastoxiv.page/@arXiv_condmatstatmech_bot/117053217162278663
- An Effective String Theory Toolbox for Quantum Hall Interfaces I: Worldsheet Kinematics and Const...
Ken K. W. Ma
https://arxiv.org/abs/2608.06097 https://mastoxiv.page/@arXiv_condmatmeshall_bot/117053183146860935
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Weighted Nuclear Elastic Net Estimation of (Near-) Low-Rank Drift Matrices in Ornstein-Uhlenbeck Processes
Dmytro Marushkevych, Francisco Pina, Mark Podolskij
https://arxiv.org/abs/2608.12838 https://arxiv.org/pdf/2608.12838 https://arxiv.org/html/2608.12838
arXiv:2608.12838v1 Announce Type: new
Abstract: We study estimation of the drift matrix in a continuously observed high-dimensional Ornstein-Uhlenbeck process when the drift is exactly or approximately low rank. In this setting, exact low rank induces non-stable directions and hence a non-ergodic regime, resulting in a poorly conditioned empirical covariance matrix. To address this difficulty, we introduce a Weighted Nuclear Elastic Net Estimator that combines ridge regularization with a nuclear-norm penalty expressed in the empirical likelihood geometry.
Under a general diagonalizable spectral framework, we establish oracle inequalities relative to arbitrary low-rank comparison matrices. For near low-rank drifts, the approximation error is naturally measured through the singular-value decay of the drift after weighting by the regularized empirical covariance. The stochastic term is controlled by self-normalized martingale arguments under appropriate choice of the tuning parameter.
For a symmetric positive-semidefinite exact low-rank model, we verify the empirical-curvature condition required to translate the weighted bound into a Frobenius-norm bound. With an appropriate choice of tuning parameters, the resulting estimator satisfies, up to a logarithmic factor, the standard rank-$r$ matrix-estimation scaling $r d/T$: specifically, its squared Frobenius error is of order $r d\log(T)/T$ with high probability, under an explicit dimension-horizon condition.
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Spectral phase transitions in Gaussian multi-index models
Florent Krzakala, Pierre Mergny, Vanessa Piccolo
https://arxiv.org/abs/2608.12183 https://arxiv.org/pdf/2608.12183 https://arxiv.org/html/2608.12183
arXiv:2608.12183v1 Announce Type: new
Abstract: Recovering a low-dimensional latent subspace from nonlinear observations of Gaussian covariates in high dimensions is a fundamental problem in feature learning. Here, we consider Gaussian multi-index models in which the covariates $\boldsymbol{x}_i \stackrel{\mathrm{i.i.d.}}{\sim} \mathcal{N}(0,\boldsymbol{I}_d)$ and the responses $\boldsymbol{y}_i$ depend on $\boldsymbol{x}_i$ only through its projection onto an unknown $r$-dimensional subspace. Earlier work based on approximate message passing (AMP) identified a sharp threshold for weak recovery [Troiani et al., 2025], raising the question of whether it can be attained, without side information, by a spectral method. We answer this affirmatively and develop a general random matrix theory for matrix-valued spectral estimators of the form \[\boldsymbol{D}_n=\frac{1}{n}\sum_{i=1}^n\boldsymbol{T}(\boldsymbol{y}_i)\otimes\boldsymbol{x}_i\boldsymbol{x}_i^\top,\] where $\boldsymbol{T}$ is an arbitrary bounded symmetric matrix-valued preprocessing map of fixed dimension. As $n,d \to \infty$ with $n/d\to\alpha$, we prove that the empirical spectral measure of $\boldsymbol{D}_n$ converges almost surely to a deterministic compactly supported distribution characterized by a matrix-valued self-consistent equation. We then establish a spectral phase transition for the largest eigenvalue: below threshold it sticks to the bulk edge, while above threshold an outlier emerges. We characterize the outlier location through a finite-dimensional deterministic equation and show that the associated spectral estimator achieves weak recovery of the latent subspace. Finally, we prove that the AMP-derived preprocessing of [Defilippis et al., 2025] is optimal among all bounded matrix-valued preprocessing maps of any fixed dimension. Its transition coincides with the AMP weak-recovery threshold, proving the general spectral conjecture of [Defilippis et al., 2025].
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