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Related papers: Noise Stability is computable and low dimensional

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Randomized experiments are the gold standard for evaluating the effects of changes to real-world systems. Data in these tests may be difficult to collect and outcomes may have high variance, resulting in potentially large measurement error.…

Machine Learning · Statistics 2018-06-27 Benjamin Letham , Brian Karrer , Guilherme Ottoni , Eytan Bakshy

The volume fluctuations in the steady state reached by a vibrated granular gas of hard particles confined by a movable piston on the top are investigated by means of event driven simulations. Also, a compressibility factor, measuring the…

Statistical Mechanics · Physics 2015-05-18 J. Javier Brey , M. J. Ruiz-Montero

Probabilistic graphical models have emerged as a powerful modeling tool for several real-world scenarios where one needs to reason under uncertainty. A graphical model's partition function is a central quantity of interest, and its…

Artificial Intelligence · Computer Science 2021-05-25 Durgesh Agrawal , Yash Pote , Kuldeep S Meel

The feasibility of computationally superior quantum computers is one of the most exciting and clear-cut scientific questions of our time. The question touches on fundamental issues regarding probability, physics, and computability, as well…

Quantum Physics · Physics 2011-06-03 Gil Kalai

It is known that evolution strategies in continuous domains might not converge in the presence of noise. It is also known that, under mild assumptions, and using an increasing number of resamplings, one can mitigate the effect of additive…

Optimization and Control · Mathematics 2014-04-10 Marie-Liesse Cauwet

We study the worst case tractability of multivariate linear problems defined on separable Hilbert spaces. Information about a problem instance consists of noisy evaluations of arbitrary bounded linear functionals, where the noise is either…

Numerical Analysis · Mathematics 2023-03-30 Leszek Plaskota , Paweł Siedlecki

We consider the model introduced by Bilu and Linial (2010), who study problems for which the optimal clustering does not change when distances are perturbed. They show that even when a problem is NP-hard, it is sometimes possible to obtain…

Machine Learning · Computer Science 2014-09-01 Shalev Ben-David , Lev Reyzin

Several continuous dynamical systems have recently been proposed as special-purpose analog computers designed to solve combinatorial optimization problems such as $k$-SAT or the Ising problem. While combinatorial optimization problems are…

Chaotic Dynamics · Physics 2025-06-17 Clemens Gneiting , Farad Khoyratee , Enrico Rinaldi , Khyati Jain , Rishab Khincha , Franco Nori

We introduce a new notion of the stability of computations, which holds under post-processing and adaptive composition. We show that the notion is both necessary and sufficient to ensure generalization in the face of adaptivity, for any…

Machine Learning · Computer Science 2020-01-01 Katrina Ligett , Moshe Shenfeld

A new vision in multidimensional statistics is proposed impacting severalareas of application. In these applications, a set of noisy measurementscharacterizing the repeatable response of a process is known as a realizationand can be seen as…

Statistics Theory · Mathematics 2016-03-11 François Léonard

Entropy notions for $\varepsilon$-incremental practical stability and incremental stability of deterministic nonlinear systems under disturbances are introduced. The entropy notions are constructed via a set of points in state space which…

Optimization and Control · Mathematics 2022-09-13 Michelle S. Chong

We show that two dynamical systems exhibiting very different deterministic behaviours possess very similar stationary distributions when stabilized by a multiplicative Gaussian white noise. We also discuss practical aspects of numerically…

Statistical Mechanics · Physics 2007-05-23 P. F. Gora

We study the stabilities of quantum states of macroscopic systems, against noises, against perturbations from environments, and against local measurements. We show that the stabilities are closely related to the cluster property, which…

Quantum Physics · Physics 2017-08-23 Akira Shimizu , Takayuki Miyadera , Akihisa Ukena

To simulate noisy boson sampling approximating it by only the lower-order multi-boson interferences (e.g., by a smaller number of interfering bosons and classical particles) is very popular idea. I show that the output data from any such…

Quantum Physics · Physics 2022-04-19 Valery Shchesnovich

An overdamped system with a linear restoring force and two multiplicative colored noises is considered. Noise amplitudes depend on the system state $x$ as $x$ and $|x|^{\alpha}$. An exactly soluble model of a system is constructed due to…

Statistical Mechanics · Physics 2007-05-23 A. N. Vitrenko

A method is suggested for treating those complicated physical problems for which exact solutions are not known but a few approximation terms of a calculational algorithm can be derived. The method permits one to answer the following rather…

High Energy Physics - Phenomenology · Physics 2009-10-31 V. I. Yukalov , E. P. Yukalova

To make arbitrarily accurate quantum computation possible, practical realization of quantum computers will require suppressing noise in quantum memory and gate operations to make it below a threshold value. A scheme based on realistic…

Quantum Physics · Physics 2007-05-23 Lu-Ming Duan , Guang-Can Guo

Noise is often regarded as anathema to quantum computation, but in some settings it can be an unlikely ally. We consider the problem of learning the class of $n$-bit parity functions by making queries to a quantum example oracle. In the…

Quantum Physics · Physics 2015-08-05 Andrew W. Cross , Graeme Smith , John A. Smolin

The paper considers a stabilizing stochastic control which can be applied to a variety of unstable and even chaotic maps. Compared to previous methods introducing control by noise, we relax assumptions on the class of maps, as well as…

Dynamical Systems · Mathematics 2019-02-25 Elena Braverman , Alexandra Rodkina

A method is provided for approximating random slow manifolds of a class of slow-fast stochastic dynamical systems. Thus approximate, low dimensional, reduced slow systems are obtained analytically in the case of sufficiently large time…

Dynamical Systems · Mathematics 2013-03-12 Jian Ren , Jinqiao Duan , Christopher K. R. T. Jones
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