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While most power system small-signal stability assessments rely on the reduced Jacobian, which depends non-linearly on the states, uncertain operating points introduce nontrivial hurdles in certifying the system's stability. In this paper,…

Systems and Control · Electrical Eng. & Systems 2019-10-04 Parikshit Pareek , Hung D. Nguyen

We give the first polynomial-time algorithm to estimate the mean of a $d$-variate probability distribution with bounded covariance from $\tilde{O}(d)$ independent samples subject to pure differential privacy. Prior algorithms for this…

Data Structures and Algorithms · Computer Science 2022-06-06 Samuel B. Hopkins , Gautam Kamath , Mahbod Majid

Triangular map is a recent construct in probability theory that allows one to transform any source probability density function to any target density function. Based on triangular maps, we propose a general framework for high-dimensional…

Machine Learning · Computer Science 2019-06-12 Priyank Jaini , Kira A. Selby , Yaoliang Yu

The three and five-dimensional convex sets of two-level complex and quaternionic quantum systems are studied in the Bayesian thermostatistical framework introduced by Lavenda. Associated with a given parameterization of each such set is a…

Quantum Physics · Physics 2007-05-23 Paul B. Slater

Win statistics have gained increasing popularity as primary analysis methods for clinical trials with hierarchical endpoints (HEs) as primary endpoints. However, existing sample size and power calculation approaches in trial design still…

Methodology · Statistics 2026-05-19 Baoshan Zhang , Huiman X. Barnhart , Yuan Wu , Roland A. Matsouaka

We introduce a spectral approach to characterizing the three-dimensional Edwards-Anderson spin glass. By analyzing the eigenvalue statistics of overlap matrices constructed from two-dimensional cross-sections, we identify a crossover from…

Disordered Systems and Neural Networks · Physics 2026-03-05 Yaprak Onder , Abbas Ali Saberi , Roderich Moessner

Deregulation of energy markets, penetration of renewables, advanced metering capabilities, and the urge for situational awareness, all call for system-wide power system state estimation (PSSE). Implementing a centralized estimator though is…

Machine Learning · Statistics 2012-07-03 Vassilis Kekatos , Georgios B. Giannakis

We calculate high-temperature graph expansions for the Ising spin glass model with 4 symmetric random distribution functions for its nearest neighbor interaction constants J_{ij}. Series for the Edwards-Anderson susceptibility \chi_EA are…

Disordered Systems and Neural Networks · Physics 2009-11-10 Daniel Daboul , Iksoo Chang , Amnon Aharony

Accurate, global Potential Energy Surfaces (PES) expressed in sum-of-products (SOP) form are a prerequisite for efficient high-dimensional quantum dynamics simulations using the MCTDH method. This work introduces a methodology for…

Chemical Physics · Physics 2026-03-31 Antoine Aerts

We present an identity for an unbiased estimate of a general statistical distribution. The identity computes the distribution density from dividing a histogram sum over a local window by a correction factor from a mean-force integral, and…

Computational Physics · Physics 2012-06-04 Cheng Zhang , Jianpeng Ma

We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary distribution over an interval $I$ which is…

Machine Learning · Computer Science 2013-05-15 Siu-On Chan , Ilias Diakonikolas , Rocco A. Servedio , Xiaorui Sun

We consider a one-step replica symmetry breaking description of the Edwards-Anderson spin glass model in 2D. The ingredients of this description are a Kikuchi approximation to the free energy and a second-level statistical model built on…

Disordered Systems and Neural Networks · Physics 2016-08-24 Gino Del Ferraro , Chuang Wang , Hai-Jun Zhou , Erik Aurell

We consider a random walk on a homogeneous space $G/\Lambda$ where $G$ is $\mathrm{SO}(2,1)$ or $\mathrm{SO}(3,1)$ and $\Lambda$ is a lattice. The walk is driven by a probability measure $\mu$ on $G$ whose support generates a Zariski-dense…

Dynamical Systems · Mathematics 2026-05-27 Timothée Bénard , Weikun He

The Lasserre/Sum-of-Squares (SoS) hierarchy is a systematic procedure for constructing a sequence of increasingly tight semidefinite relaxations. It is known that the hierarchy converges to the 0/1 polytope in n levels and captures the…

Computational Complexity · Computer Science 2015-10-08 Adam Kurpisz , Samuli Leppänen , Monaldo Mastrolilli

A new method to simulate probability distributions in regions where the events are VERY unlikely (e.g. p ~ 10^{-40}) is presented. The basic idea is to represent the underlying probability space by the phase space of a physical system. The…

Disordered Systems and Neural Networks · Physics 2009-11-07 Alexander K. Hartmann

This paper introduces a general class of hierarchical nonparametric prior distributions. The random probability measures are constructed by a hierarchy of generalized species sampling processes with possibly non-diffuse base measures. The…

Methodology · Statistics 2018-03-16 Federico Bassetti , Roberto Casarin , Luca Rossini

A Wright function based framework is proposed to combine and extend several distribution families. The $\alpha$-stable distribution is generalized by adding the degree of freedom parameter. The PDF of this two-sided super distribution…

Statistical Finance · Quantitative Finance 2025-02-18 Stephen H. Lihn

We study the problem of computing weighted sum-of-squares (WSOS) certificates for positive polynomials over a compact semialgebraic set. Building on the theory of interior-point methods for convex optimization, we introduce the concept of…

Optimization and Control · Mathematics 2022-05-09 Maria M. Davis , Dávid Papp

The authors present empirical distributions for the halting time (measured by the number of iterations to reach a given accuracy) of optimization algorithms applied to two random systems: spin glasses and deep learning. Given an algorithm,…

Machine Learning · Computer Science 2018-12-13 Levent Sagun , Thomas Trogdon , Yann LeCun

We introduce Selective Greedy Equivalence Search (SGES), a restricted version of Greedy Equivalence Search (GES). SGES retains the asymptotic correctness of GES but, unlike GES, has polynomial performance guarantees. In particular, we show…

Machine Learning · Computer Science 2015-06-09 David Maxwell Chickering , Christopher Meek