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We study the uniform query reliability problem, which asks, for a fixed Boolean query Q, given an instance I, how many subinstances of I satisfy Q. Equivalently, this is a restricted case of Boolean query evaluation on tuple-independent…

Databases · Computer Science 2023-01-18 Antoine Amarilli

This article is devoted to the construction of numerical methods which remain insensitive to the smallness of the semiclassical parameter for the linear Schr{\"o}dinger equation in the semiclassical limit. We specifically analyse the…

Analysis of PDEs · Mathematics 2018-10-15 Philippe Chartier , Loïc Le Treust , Florian Méhats

Quantum circuit equivalence checking asks whether two circuits implement the same unitary. It guarantees compiler correctness and safe optimization, yet most existing approaches scale exponentially with the number of qubits or the circuit…

Quantum Physics · Physics 2026-03-16 Daisuke Sakamoto , Soshun Naito , Yusei Mori , Kosuke Mitarai

The union-find decoder is a leading algorithmic approach to the correction of quantum errors on the surface code, achieving code thresholds comparable to minimum-weight perfect matching (MWPM) with amortised computational time scaling…

Quantum Physics · Physics 2025-04-10 Sam J. Griffiths , Dan E. Browne

Given samples from two distributions over an $n$-element set, we wish to test whether these distributions are statistically close. We present an algorithm which uses sublinear in $n$, specifically, $O(n^{2/3}\epsilon^{-8/3}\log n)$,…

Data Structures and Algorithms · Computer Science 2010-11-05 Tugkan Batu , Lance Fortnow , Ronitt Rubinfeld , Warren D. Smith , Patrick White

We study the problem of Out-of-Distribution (OOD) detection, that is, detecting whether a learning algorithm's output can be trusted at inference time. While a number of tests for OOD detection have been proposed in prior work, a formal…

Machine Learning · Statistics 2023-09-19 Akshayaa Magesh , Venugopal V. Veeravalli , Anirban Roy , Susmit Jha

Two-sample hypothesis testing for network comparison presents many significant challenges, including: leveraging repeated network observations and known node registration, but without requiring them to operate; relaxing strong structural…

Methodology · Statistics 2024-02-05 Meijia Shao , Dong Xia , Yuan Zhang , Qiong Wu , Shuo Chen

We show how any PAC learning algorithm that works under the uniform distribution can be transformed, in a blackbox fashion, into one that works under an arbitrary and unknown distribution $\mathcal{D}$. The efficiency of our transformation…

Machine Learning · Statistics 2023-03-31 Guy Blanc , Jane Lange , Ali Malik , Li-Yang Tan

Optimization by stochastic gradient descent is an important component of many large-scale machine learning algorithms. A wide variety of such optimization algorithms have been devised; however, it is unclear whether these algorithms are…

Machine Learning · Computer Science 2014-02-26 Tom Schaul , Ioannis Antonoglou , David Silver

Unevenly spaced samples from a periodic function are common in signal processing and can often be viewed as a perturbed equally spaced grid. In this paper, we analyze how the uneven distribution of the samples impacts the quality of…

Numerical Analysis · Mathematics 2023-04-11 Annan Yu , Alex Townsend

Overlapping clusters are common in models of many practical data-segmentation applications. Suppose we are given $n$ elements to be clustered into $k$ possibly overlapping clusters, and an oracle that can interactively answer queries of the…

Machine Learning · Computer Science 2019-10-29 Wasim Huleihel , Arya Mazumdar , Muriel Médard , Soumyabrata Pal

We present an adaptive algorithm with one-sided error for the problem of junta testing for Boolean function under the challenging distribution-free setting, the query complexity of which is $\widetilde O(k)/\epsilon$. This improves the…

Computational Complexity · Computer Science 2023-01-27 Xiaojin Zhang

We study the equivalence testing problem where the goal is to determine if the given two unknown distributions on $[n]$ are equal or $\epsilon$-far in the total variation distance in the conditional sampling model (CFGM, SICOMP16; CRS,…

Data Structures and Algorithms · Computer Science 2023-08-23 Diptarka Chakraborty , Sourav Chakraborty , Gunjan Kumar

We propose a projection-based class of uniformity tests on the hypersphere using statistics that integrate, along all possible directions, the weighted quadratic discrepancy between the empirical cumulative distribution function of the…

Data uniformity is a concept associated with several semantic data characteristics such as lack of features, correlation and sample bias. This article introduces a novel measure to assess data uniformity and detect uniform pointsets on…

Computational Geometry · Computer Science 2020-04-14 Panagiotis Sidiropoulos

This paper presents an algorithm that achieves hyper-arc consistency for the soft alldifferent constraint. To this end, we prove and exploit the equivalence with a minimum-cost flow problem. Consistency of the constraint can be checked in…

Programming Languages · Computer Science 2007-05-23 Willem Jan van Hoeve

For a graph $G$, let $Z(G,\lambda)$ be the partition function of the monomer-dimer system defined by $\sum_k m_k(G)\lambda^k$, where $m_k(G)$ is the number of matchings of size $k$ in $G$. We consider graphs of bounded degree and develop a…

Data Structures and Algorithms · Computer Science 2013-09-05 Marc Lelarge , Hang Zhou

In this paper, we consider a matroid generalization of the stable matching problem. In particular, we consider the setting where preferences may contain ties. For this generalization, we propose a polynomial-time algorithm for the problem…

Computer Science and Game Theory · Computer Science 2026-01-19 Naoyuki Kamiyama

$ $We study the $d$-Uniform Hypergraph Matching ($d$-UHM) problem: given an $n$-vertex hypergraph $G$ where every hyperedge is of size $d$, find a maximum cardinality set of disjoint hyperedges. For $d\geq3$, the problem of finding the…

Data Structures and Algorithms · Computer Science 2020-09-22 Oussama Hanguir , Clifford Stein

We propose a new setting for testing properties of distributions while receiving samples from several distributions, but few samples per distribution. Given samples from $s$ distributions, $p_1, p_2, \ldots, p_s$, we design testers for the…

Data Structures and Algorithms · Computer Science 2019-11-19 Maryam Aliakbarpour , Sandeep Silwal