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We study the problem of learning causal models from observational data through the lens of interpolation and its counterpart -- regularization. A large volume of recent theoretical, as well as empirical work, suggests that, in highly…

Machine Learning · Statistics 2022-02-21 Leena Chennuru Vankadara , Luca Rendsburg , Ulrike von Luxburg , Debarghya Ghoshdastidar

In this note, we extend modular techniques for computing Gr\"obner bases from the commutative setting to the vast class of noncommutative $G$-algebras. As in the commutative case, an effective verification test is only known to us in the…

Rings and Algebras · Mathematics 2017-04-11 Wolfram Decker , Christian Eder , Viktor Levandovskyy , Sharwan K. Tiwari

For a homological functor from a triangulated category to an abelian category satisfying some technical assumptions we construct a tower of interpolation categories. These are categories over which the functor factorizes and which capture…

Algebraic Topology · Mathematics 2007-09-27 Georg Biedermann

We propose a novel modular debiasing technique applicable to any discrete random source, addressing the fundamental challenge of reliably extracting high-quality randomness from inherently imperfect physical processes. The method involves…

Data Analysis, Statistics and Probability · Physics 2025-05-12 Eduardo Gueron

We present a simple method based on the stability and duality of the properties of sampling and interpolation, which allows one to substantially simplify the proofs of some classical results.

Classical Analysis and ODEs · Mathematics 2015-12-07 Alexander Olevskii , Alexander Ulanovskii

Coherent superpositions are one of the hallmarks of quantum mechanics and are vital for any quantum mechanical device to outperform the classically achievable. Generically, superpositions are verified in interference experiments, but…

Quantum Physics · Physics 2020-03-04 Benjamin Dive , Nikolaos Koukoulekidis , Stefanos Mousafeiris , Florian Mintert

The general idea of this paper is to start from a classical integrable (partial differential) equation which arises as a compatibility condition for a matrix linear differential problem. For definitiveness' sake, a generalised sinh-Gordon…

High Energy Physics - Theory · Physics 2026-05-19 Davide Fioravanti , Marco Rossi

We apply random matrix and free probability techniques to the study of linear maps of interest in quantum information theory. Random quantum channels have already been widely investigated with spectacular success. Here, we are interested in…

Quantum Physics · Physics 2019-02-27 Benoit Collins , Patrick Hayden , Ion Nechita

In this thesis we study convolutions that arise from noncommutative probability theory. We prove several regularity results for free convolutions, and for measures in partially defined one-parameter free convolution semigroups. We discuss…

Operator Algebras · Mathematics 2007-05-23 Serban Teodor Belinschi

We study interpolant extraction from local first-order refutations. We present a new theoretical perspective on interpolation based on clearly separating the condition on logical strength of the formula from the requirement on the com- mon…

Logic in Computer Science · Computer Science 2017-11-08 Bernhard Gleiss , Laura Kovacs , Martin Suda

In this paper we present an efficient algorithm for bivariate interpolation, which is based on the use of the partition of unity method for constructing a global interpolant. It is obtained by combining local radial basis function…

Numerical Analysis · Mathematics 2014-08-04 Roberto Cavoretto

In this paper we examine an inverse problem in the modular theory of von Neumann algebras in the case of finite factors. First we give a characterization of cyclic and separating vectors for finite factors in terms of operators associated…

Operator Algebras · Mathematics 2007-05-23 Stefan Boller

Maximally supersymmetric (p+1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes…

High Energy Physics - Theory · Physics 2014-12-15 Takeshi Morita , Shotaro Shiba , Toby Wiseman , Benjamin Withers

In quantum field theory, elemental particles are assumed to be point particles. As a result, the loop integrals are divergent in many cases. Regularization and renormalization are necessary in order to get the physical finite results from…

High Energy Physics - Theory · Physics 2015-05-19 P. Wang

In this paper we show how gauge symmetries in an effective theory can be used to simplify proofs of factorization formulae in highly energetic hadronic processes. We use the soft-collinear effective theory, generalized to deal with…

High Energy Physics - Phenomenology · Physics 2009-11-07 Christian W. Bauer , Sean Fleming , Dan Pirjol , Ira Z. Rothstein , Iain W. Stewart

In this note, we study the relation between Fontaine-Laffaille modules and strongly divisible modules, without assuming the main theorem of Fontaine-Laffaille (but we need to assume the main results concerning strongly divisible modules).…

Number Theory · Mathematics 2023-04-04 Hui Gao

We propose a framework for synthesizing inductive invariants for incomplete verification engines, which soundly reduce logical problems in undecidable theories to decidable theories. Our framework is based on the counter-example guided…

Programming Languages · Computer Science 2018-01-15 Daniel Neider , Pranav Garg , P. Madhusudan , Shambwaditya Saha , Daejun Park

We outline refined versions of two major quantum algorithms for performing principal component analysis and solving linear equations. Our methods are exponentially faster than their classical counterparts and even previous quantum…

Quantum Physics · Physics 2025-04-02 Nhat A. Nghiem

We use strong complementarity to introduce dynamics and symmetries within the framework of CQM, which we also extend to infinite-dimensional separable Hilbert spaces: these were long-missing features, which open the way to a wealth of new…

Quantum Physics · Physics 2017-09-29 Stefano Gogioso

We are often interested in decomposing complex, structured data into simple components that explain the data. The linear version of this problem is well-studied as dictionary learning and factor analysis. In this work, we propose a…

Machine Learning · Computer Science 2024-07-29 Avrim Blum , Kavya Ravichandran