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Postselected quantum computation is distinguished from regular quantum computation by accepting the output only if measurement outcomes satisfy predetermined conditions. The output must be accepted with nonzero probability. Methods for…

Quantum Physics · Physics 2007-05-23 E. Knill

Evaluating conditional coverage remains one of the most persistent challenges in assessing the reliability of predictive systems. Although conformal methods can give guarantees on marginal coverage, no method can guarantee to produce sets…

Machine Learning · Statistics 2025-12-15 Sacha Braun , David Holzmüller , Michael I. Jordan , Francis Bach

In the present paper, a robust approach to a special class of convex feasibility problems is considered. By techniques of convex and variational analysis, conditions for the existence of robust feasible solutions and related error bounds…

Optimization and Control · Mathematics 2025-05-06 Amos Uderzo

In this article we present our state of the art of fitting helioseismic p-mode spectra. We give a step by step recipe for fitting the spectra: statistics of the spectra both for spatially unresolved and resolved data, the use of Maximum…

Astrophysics · Physics 2009-10-30 T. Appourchaux , L. Gizon , M. C. Rabello-Soares

Parasitic extraction is a powerful tool in the design process of electromechanical devices, specifically as part of workflows that check electromagnetic compatibility. A novel scheme to extract impedances from CAD device models, suitable…

Computational Engineering, Finance, and Science · Computer Science 2021-07-07 Jonathan Stysch , Andreas Klaedtke , Herbert De Gersem

The recent paper Cand\`es et al. (2018) introduced model-X knockoffs, a method for variable selection that provably and non-asymptotically controls the false discovery rate with no restrictions or assumptions on the dimensionality of the…

Methodology · Statistics 2020-06-16 Dongming Huang , Lucas Janson

A general separability condition on the second moment (covariance matrix) for continuous variable two-party systems is derived by an analysis analogous to the derivation of the Kennard's uncertainty relation without referring to the…

Quantum Physics · Physics 2015-05-13 Kazuo Fujikawa

Preconditioning is a technique from numerical linear algebra that can accelerate algorithms to solve systems of equations. In this paper, we demonstrate how preconditioning can circumvent a stringent assumption for sign consistency in…

Statistics Theory · Mathematics 2012-08-29 Jinzhu Jia , Karl Rohe

We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability…

Probability · Mathematics 2020-03-17 Giuseppe Sanfilippo , Angelo Gilio , David Over , Niki Pfeifer

Post-selection inference has recently been proposed as a way of quantifying uncertainty about detected changepoints. The idea is to run a changepoint detection algorithm, and then re-use the same data to perform a test for a change near…

Methodology · Statistics 2026-05-11 Rachel Carrington , Paul Fearnhead

We consider the problem of principal component analysis (PCA) in the presence of outliers. Given a matrix $A$ ($d \times n$) and parameters $k, m$, the goal is to remove a set of at most $m$ columns of $A$ (known as outliers), so as to…

Data Structures and Algorithms · Computer Science 2018-05-14 Aditya Bhaskara , Srivatsan Kumar

This paper considers mathematical programs, whose constraints are expressed by a parameterized vector equilibrium problem. The latter is a well recognized framework, which is able to cover multicriteria optimization, vector variational…

Optimization and Control · Mathematics 2022-10-18 Amos Uderzo

In this paper, within a unified framework of the condition number theory we present the explicit expression of the projected condition number of the equality constrained indefinite least squares problem. By setting specific norms and…

Numerical Analysis · Mathematics 2020-07-24 Shaoxin Wang , Hanyu Li , Hu Yang

This paper studies coefficient-level, structure-preserving output-feedback stabilization of linear port-Hamiltonian (pH) descriptor systems. Existing stabilization conditions generally require explicit pH representations, which may be…

Optimization and Control · Mathematics 2026-05-15 Shuo Shi , Juan Zhang

This paper presents a new approach to conditional inference, based on the simulation of samples conditioned by a statistics of the data. Also an explicit expression for the approximation of the conditional likelihood of long runs of the…

Applications · Statistics 2012-02-07 Michel Broniatowski , Virgile Caron

The effect of a moving defect particle for the one-dimensional partially asymmetric simple exclusion process on a ring is considered. The current of the ordinary particles, the speed of the defect particle and the density profile of the…

Statistical Mechanics · Physics 2007-05-23 Tomohiro Sasamoto

Testing the significance of a variable or group of variables $X$ for predicting a response $Y$, given additional covariates $Z$, is a ubiquitous task in statistics. A simple but common approach is to specify a linear model, and then test…

Statistics Theory · Mathematics 2024-05-08 Anton Rask Lundborg , Ilmun Kim , Rajen D. Shah , Richard J. Samworth

Let F:=(f_1,...,f_n) be a random polynomial system with fixed n-tuple of supports. Our main result is an upper bound on the probability that the condition number of f in a region U is larger than 1/epsilon. The bound depends on an integral…

Numerical Analysis · Mathematics 2025-10-20 Gregorio Malajovich , J. Maurice Rojas

In this article, we consider inverse problems of determining a source term and a coefficient of a first-order partial differential equation and prove conditional stability estimates with minimum boundary observation data and relaxed…

Analysis of PDEs · Mathematics 2015-09-02 Fikret Gölgeleyen , Masahiro Yamamoto

We propose a general new method, the conditional permutation test, for testing the conditional independence of variables $X$ and $Y$ given a potentially high-dimensional random vector $Z$ that may contain confounding factors. The proposed…

Methodology · Statistics 2019-05-08 Thomas B. Berrett , Yi Wang , Rina Foygel Barber , Richard J. Samworth