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The canonical class in the realm of counting complexity is #P. It is well known that the problem of counting the models of a propositional formula in disjunctive normal form (#DNF) is complete for #P under Turing reductions. On the other…

Computational Complexity · Computer Science 2025-06-10 Max Bannach , Erik D. Demaine , Timothy Gomez , Markus Hecher

Recently, it was observed that spatially-coupled LDPC code ensembles approach the Shannon capacity for a class of binary-input memoryless symmetric (BMS) channels. The fundamental reason for this was attributed to a "threshold saturation"…

Information Theory · Computer Science 2010-10-29 Shrinivas Kudekar , Henry D. Pfister

This paper focuses on the relation between computational learning theory and resource-bounded dimension. We intend to establish close connections between the learnability/nonlearnability of a concept class and its corresponding size in…

Computational Complexity · Computer Science 2015-03-17 Ricard Gavalda , Maria Lopez-Valdes , Elvira Mayordomo , N. V. Vinodchandran

Let $p(\cdot)$ be a measurable function defined on a probability space satisfying $0<p_-:={\rm ess}\inf_{x\in \Omega}p(x)\leq {\rm ess}\sup_{x\in\Omega}p(x)=:p_+<\infty$. We investigate five types of martingale Hardy spaces $H_{p(\cdot)}$…

Probability · Mathematics 2020-01-27 Yong Jiao , Ferenc Weisz , Dejian Zhou , Lian Wu

We introduce a method for proving almost sure termination in the context of lambda calculus with continuous random sampling and explicit recursion, based on ranking supermartingales. This result is extended in three ways. Antitone ranking…

Programming Languages · Computer Science 2021-05-04 Andrew Kenyon-Roberts , Luke Ong

In a previous paper, we proved that for any submartingale $(X_t)_{t \geq 0}$ of class $(\Sigma)$, defined on a filtered probability space $(\Omega, \mathcal{F}, \mathbb{P}, (\mathcal{F}_t)_{t \geq 0})$, which satisfies some technical…

Probability · Mathematics 2009-12-25 Joseph Najnudel , Ashkan Nikeghbali

Shapley values have seen widespread use in machine learning as a way to explain model predictions and estimate the importance of covariates. Accurately explaining models is critical in real-world models to both aid in decision making and to…

Machine Learning · Statistics 2024-08-19 Daniel de Marchi , Michael Kosorok , Scott de Marchi

Multi-dimensional continuous local martingales, enhanced with their stochastic area process, give rise to geometric rough paths with a.s. finite homogenous p-variation, p>2. Here we go one step further and establish quantitative bounds of…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

For a $d$-dimensional stochastic process $(S_n)_{n=0}^N$ we obtain criteria for the existence of an equivalent martingale measure, whose density $z$, up to a normalizing constant, is bounded from below by a given random variable $f$. We…

Probability · Mathematics 2008-04-11 Dmitry B. Rokhlin

Designing large coupling memory quasi-cyclic spatially-coupled LDPC (QC-SC-LDPC) codes with low error floors requires eliminating specific harmful substructures (e.g., short cycles) induced by edge spreading and lifting. Building on our…

Information Theory · Computer Science 2026-01-21 Lei Huang

The counting and (upper) mass dimensions are notions of dimension for subsets of $\mathbb{Z}^d$. We develop their basic properties and give a characterization of the counting dimension via coverings. In addition, we prove Marstrand-type…

Dynamical Systems · Mathematics 2016-08-10 D. Glasscock

Let $X$ be a supermartingale starting from $0$ which has only nonnegative jumps. For each $0<p<1$ we determine the best constants $c_p$, $C_p$ and $\mathfrak{c}_p$ such that $$ \,\,\,\,\sup_{t\geq 0}\left|\left|X_t\right|\right|_p\leq…

Probability · Mathematics 2013-12-19 Rodrigo Bañuelos , Adam Osekowski

We introduce the concept of effective dimension for a wide class of metric spaces that are not required to have a computable measure. Effective dimension was defined by Lutz in (Lutz 2003) for Cantor space and has also been extended to…

Computational Complexity · Computer Science 2017-05-16 Elvira Mayordomo

Stemming from information-theoretic learning, the correntropy criterion and its applications to machine learning tasks have been extensively explored and studied. Its application to regression problems leads to the robustness enhanced…

Machine Learning · Computer Science 2020-07-23 Yunlong Feng

We analyse the entanglement structure of states generated by random constant-depth two-dimensional quantum circuits, followed by projective measurements of a subset of sites. By deriving a rigorous lower bound on the average entanglement…

Quantum Physics · Physics 2025-05-21 Max McGinley , Wen Wei Ho , Daniel Malz

Magnitude of a finite metric space and the related notion of magnitude functions on metric spaces is an active area of research in algebraic topology. Magnitude originally arose in the context of biology, where it represents the number of…

Algebraic Topology · Mathematics 2019-08-08 Glenn Fung , Eric Bunch , Dan Dickinson

We derive sharp lower bounds for L^p-functions on the n-dimensional unit hypercube in terms of their p-th marginal moments. Such bounds are the unique solutions of a system of constrained nonlinear integral equations depending on the…

Probability · Mathematics 2021-01-12 Paolo Guasoni , Eberhard Mayerhofer , Mingchuan Zhao

We propose a new complexity measure of space for the BSS model of computation. We define LOGSPACE\_W and PSPACE\_W complexity classes over the reals. We prove that LOGSPACE\_W is included in NC^2\_R and in P\_W, i.e. is small enough for…

Computational Complexity · Computer Science 2016-08-16 Paulin Jacobé De Naurois

We introduce a quantitative version of Property A in order to estimate the L^p-compressions of a metric measure space X. We obtain various estimates for spaces with sub-exponential volume growth. This quantitative property A also appears to…

Metric Geometry · Mathematics 2007-06-28 Romain Tessera

We investigate temporal correlations in the simplest measurement scenario, i.e., that of a physical system on which the same measurement is performed at different times, producing a sequence of dichotomic outcomes. The resource for…

Quantum Physics · Physics 2022-01-19 Lucas B. Vieira , Costantino Budroni