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We consider the problem of upper bounding the expected log-likelihood sub-optimality of the maximum likelihood estimate (MLE), or a conjugate maximum a posteriori (MAP) for an exponential family, in a non-asymptotic way. Surprisingly, we…

Machine Learning · Statistics 2021-11-15 Rémi Le Priol , Frederik Kunstner , Damien Scieur , Simon Lacoste-Julien

We generalize a version of Lavrent\'ev's theorem which says that a function that is continuous on a compact set K with connected complement and without interior points can be uniformly approximated as closely as desired by a polynomial…

Complex Variables · Mathematics 2019-07-02 Johan Andersson , Linnea Rousu

Different techniques have been used to prove several transference theorems of the form "nontrivial algorithms for a circuit class C yield circuit lower bounds against C". In this survey we revisit many of these results. We discuss how…

Computational Complexity · Computer Science 2013-09-03 Igor C. Oliveira

In recent years, there has been a flurry of activity towards proving lower bounds for homogeneous depth-4 arithmetic circuits, which has brought us very close to statements that are known to imply $\textsf{VP} \neq \textsf{VNP}$. It is open…

Computational Complexity · Computer Science 2018-06-19 Mrinal Kumar , Shubhangi Saraf

We improve the best known lower bounds on the exponential behavior of the maximum of the number of connected sets, $N(G)$, and dominating connected sets, $N_{dom}(G)$, for regular graphs. These lower bounds are improved by constructing a…

Combinatorics · Mathematics 2024-09-27 Stijn Cambie , Jan Goedgebeur , Jorik Jooken

Thanks to earlier work of Koiran, it is known that the truth of the Generalized Riemann Hypothesis (GRH) implies that the dimension of algebraic sets over the complex numbers can be determined within the polynomial-hierarchy. The truth of…

Computational Complexity · Computer Science 2018-03-13 J. Maurice Rojas , Yuyu Zhu

We show that common choices of kernel functions for a highly accurate and massively scalable nearest-neighbour based GP regression model (GPnn: \cite{GPnn}) exhibit gradual convergence to asymptotic behaviour as dataset-size $n$ increases.…

Statistics Theory · Mathematics 2024-04-10 Anthony Stephenson , Robert Allison , Edward Pyzer-Knapp

Stochastic differential equations (SDEs) and the Kolmogorov partial differential equations (PDEs) associated to them have been widely used in models from engineering, finance, and the natural sciences. In particular, SDEs and Kolmogorov…

Numerical Analysis · Mathematics 2021-10-05 Christian Beck , Sebastian Becker , Philipp Grohs , Nor Jaafari , Arnulf Jentzen

We introduce a method for the theoretical analysis of exponential random graph models. The method is based on a large-deviations approximation to the normalizing constant shown to be consistent using theory developed by Chatterjee and…

Probability · Mathematics 2013-11-21 Sourav Chatterjee , Persi Diaconis

This paper studies numerical methods for the approximation of elliptic PDEs with lognormal coefficients of the form $-{\rm div}(a\nabla u)=f$ where $a=\exp(b)$ and $b$ is a Gaussian random field. The approximant of the solution $u$ is an…

Numerical Analysis · Mathematics 2021-03-26 Albert Cohen , Giovanni Migliorati

We define a reduction mechanism for LP and SDP formulations that degrades approximation factors in a controlled fashion. Our reduction mechanism is a minor restriction of classical reductions establishing inapproximability in the context of…

Computational Complexity · Computer Science 2016-01-20 Gábor Braun , Sebastian Pokutta , Daniel Zink

Partial Differential Equations (PDE) are fundamental to model different phenomena in science and engineering mathematically. Solving them is a crucial step towards a precise knowledge of the behaviour of natural and engineered systems. In…

The numerous phenomenological equations used in the study of the behaviour of single-domain magnetic nanoparticles are described and some issues clarified by means of qualitative comparison. To enable a quantitative \textit{application} of…

Mesoscale and Nanoscale Physics · Physics 2014-01-29 Zs. Janosfalvi , J. Hakl , P. F. de Chatel

The goal of this work is to fill a gap in [Yang, SIAM J. Matrix Anal. Appl, 41 (2020), 1797--1825]. In that work, an approximation procedure was proposed for orthogonal low-rank tensor approximation; however, the approximation lower bound…

Optimization and Control · Mathematics 2021-01-01 Yuning Yang

We consider deterministic particle dynamics with time evolving weights and their associated Kolmogorov equation and mean-field equation. We prove existence and unique- ness for the limit PDE alongside estimates on the growth of the…

Analysis of PDEs · Mathematics 2026-03-06 Immanuel Ben Porat , José A. Carrillo , Alexandra Holzinger

This paper develops an enhanced finite element method for approximating a class of variational problems which exhibit the \textit{Lavrentiev gap phenomenon} in the sense that the minimum values of the energy functional have a nontrivial gap…

Numerical Analysis · Mathematics 2016-10-12 Xiaobing Feng , Stefan Schnake

We prove that $poly(t) \cdot n^{1/D}$-depth local random quantum circuits with two qudit nearest-neighbor gates on a $D$-dimensional lattice with n qudits are approximate $t$-designs in various measures. These include the "monomial"…

Quantum Physics · Physics 2023-05-05 Aram Harrow , Saeed Mehraban

We apply the discontinuous Galerkin finite element method with a degree $p$ polynomial basis to the linear advection equation and derive a PDE which the numerical solution solves exactly. We use a Fourier approach to derive polynomial…

Numerical Analysis · Mathematics 2015-01-22 Noel Chalmers , Lilia Krivodonova

We study an approximate version of $q$-query LDCs (Locally Decodable Codes) over the real numbers and prove lower bounds on the encoding length of such codes. A $q$-query $(\alpha,\delta)$-approximate LDC is a set $V$ of $n$ points in…

Computational Complexity · Computer Science 2014-02-28 Jop Briët , Zeev Dvir , Guangda Hu , Shubhangi Saraf

It is well-known that an algorithm exists which approximates the NP-complete problem of Set Cover within a factor of ln(n), and it was recently proven that this approximation ratio is optimal unless P = NP. This optimality result is the…

Computational Complexity · Computer Science 2021-11-30 Erika Melder