Tootfinder

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- A new kernel-based approach for the global sensitivity analysis of models with correlated inputs
Troy Larsen, Alen Alexanderian
https://arxiv.org/abs/2603.00849 https://mastoxiv.page/@arXiv_mathST_bot/116164541348754007
- Identifiability, Convergence and Nonparametric Estimation of Bivariate Archimax Copulas
Nicolas Dietrich, Wolfgang Trutschnig
https://arxiv.org/abs/2607.19087 https://mastoxiv.page/@arXiv_mathST_bot/116962627413524469
- Proper Bayes minimax multiple shrinkage estimation
Pankaj Bhagwat, William E. Strawderman, Edward I. George
https://arxiv.org/abs/2607.23717 https://mastoxiv.page/@arXiv_mathST_bot/116996538414904121
- Local Second-Order Bounds for Aggregation-Order Variation in Density Fusion
Ratan Bahadur Thapa
https://arxiv.org/abs/2608.01420 https://mastoxiv.page/@arXiv_mathST_bot/117036312800349457
- Debiased Causal Mediation Analysis in Ultra-High-Dimensional Settings in the Presence of Interact...
Shi Bo, AmirEmad Ghassami, Debarghya Mukherjee
https://arxiv.org/abs/2412.08827 https://mastoxiv.page/@arXiv_statME_bot/113644641256825402
- Schnorr Randomness and Effective Bayesian Consistency and Inconsistency
Simon M. Huttegger, Sean Walsh, Francesca Zaffora Blando
https://arxiv.org/abs/2501.11210 https://mastoxiv.page/@arXiv_mathLO_bot/113872370795037324
- Semiparametric Inference for Half-Trek Estimators in Linear Structural Equation Models
Leopold Mareis, Nils Sturma, Mathias Drton
https://arxiv.org/abs/2606.26931 https://mastoxiv.page/@arXiv_statME_bot/116815434864895376
- A Bayesian Proof of the Bernoulli Theorem
Jingbo Liu, Ilias Zadik
https://arxiv.org/abs/2608.11031 https://mastoxiv.page/@arXiv_mathPR_bot/117081540858079561
- The Geometry of Cochains on Sampled Vietoris-Rips Complexes
Darrick Lee, Kelly Maggs
https://arxiv.org/abs/2608.11137 https://mastoxiv.page/@arXiv_mathDG_bot/117081537320356423
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Google rolls out Gemini 4 Argon globally via the Gemini API and to Google AI Pro subscribers in the Gemini app and AI Mode, and in Antigravity for Ultra users (Robert Hart/The Verge)
https://www.theverge.com/ai-artificial-intelligence/1009862/google…

Google finally releases Gemini 4 Argon
Google has been trailing its rivals for months, but says Argon can compete with top models like Anthropic’s Fable and OpenAI’s GPT-6 Astra.

Is it Carson Beck time in Arizona? When Cardinals need to replace Jacoby Brissett with the rookie QB

https://www.cbssports.com/nfl/news/should-cardinals-replace-jacoby-brissett-…

Replaced article(s) found for math.GN. https://arxiv.org/list/math.GN/new
[1/1]:
- Functional countability and exponential separability of product spaces and subspaces
Rodrigo Hern\'andez-Guti\'errez, Santi Spadaro
https://arxiv.org/abs/2603.02018 https://mastoxiv.page/@arXiv_mathGN_bot/116164252853318763
- Nonembeddable contractible open manifolds arising from Whitehead doubling
Shijie Gu, Jian Wang, Yanqing Zou
https://arxiv.org/abs/2510.06598 https://mastoxiv.page/@arXiv_mathGT_bot/115343350914417175
toXiv_bot_toot

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Geometric Identification and Consistent Estimation of Source Apportionment with Application to Gr...
Bora Jin, Nicholas J. Spada, Jessie Creamean, Matthew Shupe, Abhirup Datta
https://arxiv.org/abs/2510.03616 https://mastoxiv.page/@arXiv_mathST_bot/115331987049793537
- Kernel Estimation Of Chatterjee's Dependence Coefficient
Mona Azadkia, Holger Dette
https://arxiv.org/abs/2602.14206 https://mastoxiv.page/@arXiv_mathST_bot/116085283519968859
- Shape without scale: an identifiability dichotomy for a bounded tail observed through a non-addit...
Jiarui Qi
https://arxiv.org/abs/2609.27384 https://mastoxiv.page/@arXiv_mathST_bot/117324926550805284
- Spectral Analysis of Gaussian Integral Operators Arising in BHEP Tests
Bruno Ebner, Dominic Edelmann, Norbert Henze, Fr\'ed\'eric Ouimet, Donald Richards
https://arxiv.org/abs/2609.28464 https://mastoxiv.page/@arXiv_mathST_bot/117325006460286578
- Allocation Stability and Wald Inference under Variance-Aware UCB
Yingying Fan, Yuxuan Han, Jinchi Lv, Xiaocong Xu, Zhengyuan Zhou
https://arxiv.org/abs/2412.08843 https://mastoxiv.page/@arXiv_statML_bot/113644645066030071
- Cascaded Multiwire-PLC/Multiple-VLC System: Characterization and Performance
Silva, Silva, Tom\'e, Figueiredo, da Silva, de Souza
https://arxiv.org/abs/2506.06357 https://mastoxiv.page/@arXiv_eessSP_bot/114658385767724324
- Set-Valued Policy Learning
Laura Fuentes-Vicente, Mathieu Even, Ga\"elle Dormion, Antoine Chambaz, Uri Shalit, Julie Josse
https://arxiv.org/abs/2605.19830 https://mastoxiv.page/@arXiv_csLG_bot/116606031645633121
- Weighted NPMLE for the Marginal Mean of Recurrent Events with a Competing Terminal Event
Anna Bellach, Michael R. Kosorok
https://arxiv.org/abs/2605.25934 https://mastoxiv.page/@arXiv_statME_bot/116639957142027974
- Semi-Supervised Kernel Ridge Fr\'echet Regression
Jaehee Seo, Kwangho Kim, Jisu Kim
https://arxiv.org/abs/2610.05388 https://mastoxiv.page/@arXiv_statME_bot/117393144890023611
- Sample-Optimal Estimation of the Fr\'echet Inception Distance
Ziyun Chen, Jerry Li, Kevin Tian, Yusong Zhu
https://arxiv.org/abs/2610.07114 https://mastoxiv.page/@arXiv_csLG_bot/117398732519059948
toXiv_bot_toot

Replaced article(s) found for math.CV. https://arxiv.org/list/math.CV/new
[1/1]:
- Singularity of non-pluripolar cohomology classes
Duc-Bao Nguyen, Shuang Su, Duc-Viet Vu
https://arxiv.org/abs/2508.14669 https://mastoxiv.page/@arXiv_mathCV_bot/115065656430154433
- Analytic structure of $q$-pseudoconcave subsets of continuous graphs
Filippo Valnegri
https://arxiv.org/abs/2603.04967 https://mastoxiv.page/@arXiv_mathCV_bot/116181309294452296
- Non-symmetric vector dyson equations
Jiaoyang Huang, Zhonggen Su, Ruizhe Xu
https://arxiv.org/abs/2607.16333 https://mastoxiv.page/@arXiv_mathCV_bot/116956844212485469
- Cofinite Zeros of High Derivatives
Eric Hou
https://arxiv.org/abs/2607.20816 https://mastoxiv.page/@arXiv_mathCV_bot/116973837268195335
- Coefficient Problems for a Ma-Minda Convex Class Associated with the Normalized Arcsine Mapping
Shantanu Panja, Abhijit Banerjee, Jhilik Banerjee, Sujoy Majumder
https://arxiv.org/abs/2607.27293 https://mastoxiv.page/@arXiv_mathCV_bot/117013548331556229
- Skoda division theorem on compact K\"ahler manifolds for line bundles with singular hermitian met...
Jaehoon Jeong
https://arxiv.org/abs/2607.29669 https://mastoxiv.page/@arXiv_mathCV_bot/117030527056701741
- Classes of Holomorphic Multicomplex-Valued Functions Generated by Elliptic-Admissible Involutions
Nicolas Doyon, Pierre-Olivier Paris\'e, William Verreault
https://arxiv.org/abs/2211.13875
- Fast vanishing cycles on perturbations of complex weighted-homogeneous complete intersection germs
Dmitry Kerner, Rodrigo Mendes
https://arxiv.org/abs/2311.13423 https://mastoxiv.page/@arXiv_mathAG_bot/111458171750230260
toXiv_bot_toot

With the extremely well-founded concern about North Korea, I do want to be careful not to revive all the barenaked racism and xenophobia of the anti-outsourcing arguments from 20 years ago. Not that any replies are doing so yet; it's just a danger that’s lurking here.
Per this conversation in the replies, when offshoring does a faceplant, it’s is almost always about the client company’s dysfunction •first•, the overseas team second, and the innate general properties of people from that other country…um, not at all:
https://hachyderm.io/@skinnylatte/117265404729717952
So let's just stay clear on that. If scammy emails like the one in the OP are actually finding traction in the US, then that's a sign of rot •in the US•.

Countable Functionally Balanced Groups
Li-Hong Xie, Jiang Yang
https://arxiv.org/abs/2608.12494 https://arxiv.org/pdf/2608.12494 https://arxiv.org/html/2608.12494
arXiv:2608.12494v1 Announce Type: new
Abstract: We prove that every countable Hausdorff functionally balanced topological group is balanced, answering Question~13 in the problem list of Bouziad and Troallic. The proof does not assume metrizability, first countability, sequentiality, or a non-Archimedean local base. Its non-locally-precompact part combines an infinite-fibre amplification, a simultaneous Bernoulli colouring lemma for countably many arbitrary self-maps, a McShane extension with respect to a continuous left-invariant pseudometric, and the Protasov--Saryev criterion. We also prove a countable-union form of Question~4: in an \(\FSIN\) group, every left uniformly discrete family whose union is countable is right uniformly discrete. Consequently, Questions~7 and~8 have positive answers for \(\aleph_0\)-bounded \(\FSIN\) groups. We reconstruct all thirteen questions and their logical relations. The original problem chapter states, without proof, that a positive answer to Question~13 would imply Question~4 for all \(\aleph_0\)-bounded groups. We isolate the ambient reflection principle needed for that transfer and explain why neither subgroup reduction nor the present colouring proof establishes it. Therefore Question~12 is \emph{not} claimed as solved here: the precise boundary between the proved countable theorem and the asserted \(\aleph_0\)-bounded transfer is recorded explicitly.
toXiv_bot_toot

Guest author Peter Firmstone continues his exploration of #security baked into the #JVM.
This 5th part is about what the caller is then allowed to do:
how incoming arguments are validated before they become objects,
why permissions are granted to what the code is, rather than where it came f…

Drift Estimation for a Multi-Dimensional L\'evy-Driven Stochastic Differential Equation Using Deep Neural Networks
Taisei Noguchi, Teppei Ogihara
https://arxiv.org/abs/2610.09813 https://arxiv.org/pdf/2610.09813 https://arxiv.org/html/2610.09813
arXiv:2610.09813v1 Announce Type: new
Abstract: We develop a non-asymptotic theory for nonparametric drift estimation in discretely observed multi-dimensional L\'evy-driven stochastic differential equations using sparse ReLU neural networks. Under exponential \(\beta\)-mixing and an exponential-tail condition on the L\'evy measure, we establish an oracle inequality for the least-squares estimator. The jump component changes both the martingale structure and the concentration regime relative to diffusion models: continuous martingales are replaced by discontinuous martingales, while the relevant empirical-process fluctuations are sub-exponential rather than sub-Gaussian. We handle these difficulties without truncating the observed increments, using an exponential-supermartingale argument for compensated Poisson integrals and \(\psi_1\)-chaining. Despite the weaker concentration, the resulting statistical bound is, up to constants, of the same order as the corresponding diffusion bound. For drift functions with hierarchical compositional structure, this yields intrinsic-dimensional convergence rates. The framework allows infinite jump activity and, in some cases, infinite variation. Finally, we establish a minimax lower bound on a fixed non-trivial compound-Poisson submodel. Together with the upper bound, this shows that the estimator is minimax optimal up to logarithmic factors.
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