English
Related papers

Related papers: Forcing with random variables in bounded arithmeti…

200 papers

For a relational structure ${\mathbb X}$ we investigate the partial order $\langle {\mathbb P} ({\mathbb X}) ,\subset \rangle$, where ${\mathbb P} ({\mathbb X}):=\{ f[X]: f\in \mathop{\rm Emb}\nolimits ({\mathbb X})\}$. Here we consider…

Logic · Mathematics 2024-04-24 Miloš S. Kurilić

Taking symmetric extensions can be considered as a generalisation of forcing, which produces a richer multiverse of models with and without the axiom of choice. We can study the structure of this multiverse using modal logic. In particular,…

Logic · Mathematics 2026-05-08 Hope Duncan

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalising constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and…

Computation · Statistics 2016-02-12 Richard G. Everitt , Adam M. Johansen , Ellen Rowing , Melina Evdemon-Hogan

As a paradigm for sequential decision making in unknown environments, reinforcement learning (RL) has received a flurry of attention in recent years. However, the explosion of model complexity in emerging applications and the presence of…

Machine Learning · Statistics 2025-07-22 Yuejie Chi , Yuxin Chen , Yuting Wei

We prove a variation of Easton's lemma for strongly proper forcings, and use it to prove that, unlike the stronger principle $\textsf{IGMP}$, $\textsf{GMP}$ together with $2^\omega \le \omega_2$ is consistent with the existence of an…

Logic · Mathematics 2019-02-20 Sean Cox , John Krueger

Variable selection is fundamental to high-dimensional statistical modeling. Many variable selection techniques may be implemented by maximum penalized likelihood using various penalty functions. Optimizing the penalized likelihood function…

Statistics Theory · Mathematics 2007-06-13 David R. Hunter , Runze Li

Sampling-based decoding underlies complex reasoning in large language models (LLMs), where decoding strategies critically shape model behavior. Temperature- and truncation-based methods reshape the next-token distribution through global…

Artificial Intelligence · Computer Science 2026-02-02 Yixin Yang , Qingxiu Dong , Zhifang Sui

Forcing axioms are generalizations of Baire category principles that allow one to intersect more dense open sets and to do so in a wider variety of circumstances. In this paper we introduce two new forcing axioms related to posets which…

Logic · Mathematics 2025-02-05 Thomas Gilton

The forcing of particles in turbulent environments influences dynamical properties pertinent to many fundamental applications involving particle-flow interactions. Current study explores the determination of forcing for one-way coupled…

Fluid Dynamics · Physics 2026-02-17 Daniel Domínguez-Vázquez , Qi Wang , Gustaaf B. Jacobs

Let G be a graph with a perfect matching. A complete forcing set of G is a subset of edges of G to which the restriction of every perfect matching is a forcing set of it. The complete forcing number of G is the minimum cardinality of…

Combinatorics · Mathematics 2021-02-09 Xin He , Heping Zhang

We use cosmological constraints from current data sets and a figure of merit (FoM) approach to probe any deviations from general relativity (GR) at cosmological scales. The FoM approach is used to study the constraining power of various…

Cosmology and Nongalactic Astrophysics · Physics 2011-12-30 Jason Dossett , Jacob Moldenhauer , Mustapha Ishak

McDiarmid's inequality has recently been proposed as a tool for setting margin requirements for complex systems. If $F$ is the bounded output of a complex system, depending on a vector of $n$ bounded inputs, this inequality provides a bound…

Statistics Theory · Mathematics 2013-08-16 Timothy C. Wallstrom

Let M denote the space of Borel probability measures on the real line. For every nonnegative t we consider the transformation $\mathbb B_t : M \to M$ defined for any given element in M by taking succesively the the (1+t) power with respect…

Operator Algebras · Mathematics 2008-08-19 Serban T. Belinschi , Alexandru Nica

In inference problems involving a multi-dimensional parameter $\theta$, it is often natural to consider decision rules that have a risk which is invariant under some group $G$ of permutations of $\theta$. We show that this implies that the…

Methodology · Statistics 2014-07-01 Erik van Zwet

Background: Mendelian randomization (MR) is a useful approach to causal inference from observational studies when randomised controlled trials are not feasible. However, study heterogeneity of two association studies required in MR is often…

Methodology · Statistics 2021-12-16 Linyi Zou , Hui Guo , Carlo Berzuini

We propose a unified theory of generalized weights for linear codes endowed with an arbitrary distance. Instead of relying on supports or anticodes, the weights of a code are defined via the intersections of the code with a chosen family of…

Information Theory · Computer Science 2025-12-22 Andrea Di Giusto , Elisa Gorla , Alberto Ravagnani

A random set is a generalisation of a random variable, i.e. a set-valued random variable. The random set theory allows a unification of other uncertainty descriptions such as interval variable, mass belief function in Dempster-Shafer theory…

Numerical Analysis · Mathematics 2018-11-27 Truong-Vinh Hoang , Hermann G. Matthies

We show that many principles of first-order arithmetic, previously only known to lie strictly between $\Sigma_1$-induction and $\Sigma_2$-induction, are equivalent to the well-foundedness of $\omega^\omega$. Among these principles are the…

Logic · Mathematics 2015-12-15 Alexander P. Kreuzer , Keita Yokoyama

We study the problem of coalitional manipulation---where $k$ manipulators try to manipulate an election on $m$ candidates---under general scoring rules, with a focus on the Borda protocol. We do so both in the weighted and unweighted…

Data Structures and Algorithms · Computer Science 2017-08-17 Orgad Keller , Avinatan Hassidim , Noam Hazon

Discrete Markov random fields form a natural class of models to represent images and spatial data sets. The use of such models is, however, hampered by a computationally intractable normalising constant. This makes parameter estimation and…

Computation · Statistics 2015-05-25 Haakon Michael Austad , Håkon Tjelmeland
‹ Prev 1 4 5 6 7 8 10 Next ›