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For better learning, large datasets are often split into small batches and fed sequentially to the predictive model. In this paper, we study such batch decompositions from a probabilistic perspective. We assume that data points (possibly…

Machine Learning · Computer Science 2025-04-10 Ghurumuruhan Ganesan

This study focuses on large deviation principles for fully coupled multiscale multivalued stochastic systems, in which the slow component is governed by a multivalued stochastic differential equation and the fast component is described by a…

Probability · Mathematics 2025-12-12 Huijie Qiao

$\ell_1$ optimization is a well known heuristic often employed for solving various forms of sparse linear problems. In this paper we look at its a variant that we refer to as the \emph{partial} $\ell_1$ and discuss its mathematical…

Optimization and Control · Mathematics 2016-12-23 Mihailo Stojnic

Given an $n$-dimensional random vector $X^{(n)}$ , for $k < n$, consider its $k$-dimensional projection $\mathbf{a}_{n,k}X^{(n)}$, where $\mathbf{a}_{n,k}$ is an $n \times k$-dimensional matrix belonging to the Stiefel manifold…

Probability · Mathematics 2021-05-12 Steven Soojin Kim , Kavita Ramanan

We study an analogue of the large deviation principle for mixed measures associated with a class of $\log$-concave probability measures whose densities depend on the gauge function of a convex body. For convex bodies in $\mathbb{R}^n$, we…

Probability · Mathematics 2026-02-25 Malak Lafi , Artem Zvavitch

Let $L$ be a holomorphic line bundle on a compact complex manifold $X$ of dimension $n,$ and let $e^{-\phi}$ be a continuous metric on $L.$ Fixing a measure $d\mu$ on $X$ gives a sequence of Hilbert spaces consisting of holomorphic sections…

Complex Variables · Mathematics 2008-05-20 Robert Berman , David Witt Nystrom

We derive an annealed large deviation principle (LDP) for the normalised and rescaled local times of a continuous-time random walk among random conductances (RWRC) in a time-dependent, growing box in $\Z^d$. We work in the interesting case…

Probability · Mathematics 2013-08-22 Wolfgang König , Tilman Wolff

In proving large deviation estimates, the lower bound for open sets and upper bound for compact sets are essentially local estimates. On the other hand, the upper bound for closed sets is global and compactness of space or an exponential…

Probability · Mathematics 2015-10-20 Chiranjib Mukherjee , S. R. S. Varadhan

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states, and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies,…

Statistical Mechanics · Physics 2018-04-25 Ushnish Ray , Garnet Kin-Lic Chan , David T. Limmer

One-dimensional run-and-tumble processes may converge towards some localized non-equilibrium steady state when the two velocities and/or the two switching rates are space-dependent. A long dynamical trajectory can be then analyzed via the…

Statistical Mechanics · Physics 2021-08-23 Cecile Monthus

We study large deviations of the size of the largest connected component in a general class of inhomogeneous random graphs with iid weights, parametrized so that the degree distribution is regularly varying. We derive a large-deviation…

Probability · Mathematics 2024-07-02 Joost Jorritsma , Bert Zwart

We extend the Gibbs conditioning principle to an abstract setting combining infinitely many linear equality constraints and non-linear inequality constraints, which need not be convex. A conditional large large deviation principle (LDP) is…

Functional Analysis · Mathematics 2024-10-29 Louis-Pierre Chaintron , Giovanni Conforti , Julien Reygner

We study the large deviations principle (LDP) for stationary solutions of a class of stochastic differential equations (SDE) in infinite time intervals by the weak convergence approach, and then establish the LDP for the invariant measures…

Probability · Mathematics 2022-06-07 Peipei Gao , Yong Liu , Yue Sun , Zuohuan Zheng

In this paper, we introduce a mathematical apparatus that is relevant for understanding a dynamical system with small random perturbations and coupled with the so-called transmutation process -- where the latter jumps from one mode to…

Dynamical Systems · Mathematics 2017-09-15 Getachew K. Befekadu

We study the dominant effect of a long wavelength density perturbation $\delta(\lambda_L)$ on short distance physics. In the non-relativistic limit, the result is a uniform acceleration, fixed by the equivalence principle, and typically has…

Cosmology and Nongalactic Astrophysics · Physics 2016-01-27 Tobias Baldauf , Mehrdad Mirbabayi , Marko Simonović , Matias Zaldarriaga

We consider a class of particle systems generalizing the $\beta$-Ensembles from random matrix theory. In these new ensembles, particles experience repulsion of power $\beta>0$ when getting close, which is the same as in the…

Probability · Mathematics 2014-01-28 Martin Venker

In ergodic physical systems, time-averaged quantities converge (for large times) to their ensemble-averaged values. Large deviation theory describes rare events where these time averages differ significantly from the corresponding ensemble…

Statistical Mechanics · Physics 2020-05-20 Robert L. Jack

We prove a large deviations principle for the largest eigenvalue of a class of biorthogonal and multiple orthogonal polynomial ensembles that includes a matrix model of Lueck, Sommers and Zirnbauer for disordered bosons and Angelesco…

Mathematical Physics · Physics 2015-03-04 Katrin Credner , Peter Eichelsbacher

We consider upper exponential bounds for the probability of the event that an absolute deviation of sample mean from mathematical expectation p is bigger comparing with some ordered level epsilon. These bounds include 2 coefficients {alpha,…

Probability · Mathematics 2010-04-13 Vladimir Nikulin

Large deviations principle is obtained for terminating multidimensional compound renewal processes. We also obtained the asymptotic of large deviations for the case when a Gibbs change of the original probability measure takes place. The…

Probability · Mathematics 2021-12-20 A. Logachov , A. Mogulskii , E. Prokopenko
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