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We consider the problem of identifying, from its first $m$ noisy moments, a probability distribution on $[0,1]$ of support $k<\infty$. This is equivalent to the problem of learning a distribution on $m$ observable binary random variables…

Machine Learning · Computer Science 2020-09-08 Spencer Gordon , Bijan Mazaheri , Leonard J. Schulman , Yuval Rabani

There has been a surge of progress in recent years in developing algorithms for testing and learning quantum states that achieve optimal copy complexity. Unfortunately, they require the use of entangled measurements across many copies of…

Quantum Physics · Physics 2020-04-20 Sebastien Bubeck , Sitan Chen , Jerry Li

We consider the problem of robustly testing the norm of a high-dimensional sparse signal vector under two different observation models. In the first model, we are given $n$ i.i.d. samples from the distribution…

Information Theory · Computer Science 2022-11-08 Anand Jerry George , Clément L. Canonne

We show posterior convergence for the community structure in the planted bi-section model, for several interesting priors. Examples include where the label on each vertex is iid Bernoulli distributed, with some parameter $r\in(0,1)$. The…

Statistics Theory · Mathematics 2021-08-16 J. van Waaij , B. J. K. Kleijn

We consider the problem of testing distribution identity. Given a sequence of independent samples from an unknown distribution on a domain of size n, the goal is to check if the unknown distribution approximately equals a known distribution…

Data Structures and Algorithms · Computer Science 2009-10-20 Krzysztof Onak

In clinical and epidemiological research doubly truncated data often appear. This is the case, for instance, when the data registry is formed by interval sampling. Double truncation generally induces a sampling bias on the target variable,…

Methodology · Statistics 2023-01-11 Jacobo de Uña-Álvarez

We establish a lower bound for deciding the satisfiability of the conjunction of any two Boolean formulas from a set called a full representation of Boolean functions of $n$ variables - a set containing a Boolean formula to represent each…

Computational Complexity · Computer Science 2014-06-24 Samuel C. Hsieh

We present an $\tilde{O}(n^{2/3}/\epsilon^2)$-query algorithm that tests whether an unknown Boolean function $f\colon\{0,1\}^n\rightarrow \{0,1\}$ is unate (i.e., every variable is either non-decreasing or non-increasing) or $\epsilon$-far…

Data Structures and Algorithms · Computer Science 2019-04-11 Xi Chen , Erik Waingarten

We provide an example of a monotone Boolean function on the hypercube given by a low depth decision tree that is not well approximated by any k-junta for small k.

Discrete Mathematics · Computer Science 2013-06-17 Daniel M. Kane

We prove a lower bound of $\Omega(n^{1/2 - c})$, for all $c>0$, on the query complexity of (two-sided error) non-adaptive algorithms for testing whether an $n$-variable Boolean function is monotone versus constant-far from monotone. This…

Computational Complexity · Computer Science 2014-12-19 Xi Chen , Anindya De , Rocco A. Servedio , Li-Yang Tan

In this work, we consider the problem of sampling a $k$-clique in a graph from an almost uniform distribution in sublinear time in the general graph query model. Specifically the algorithm should output each $k$-clique with probability…

Data Structures and Algorithms · Computer Science 2020-12-09 Talya Eden , Dana Ron , Will Rosenbaum

We investigate intermittent diffusion using cycle expansions, and show that a truncation based on cycle stability achieves reasonable convergence.

chao-dyn · Physics 2009-10-30 Carl Dettmann , Predrag Cvitanovic'

We consider the best-choice problem for independent (not necessarily iid) observations $X_1, \cdots, X_n$ with the aim of selecting the sample minimum. We show that in this full generality the monotone case of optimal stopping holds and the…

Probability · Mathematics 2021-10-13 Alexander Gnedin , Patryk Kozieł , Małgorzata Sulkowska

The overestimation bias is one of the major impediments to accurate off-policy learning. This paper investigates a novel way to alleviate the overestimation bias in a continuous control setting. Our method---Truncated Quantile Critics,…

Machine Learning · Computer Science 2020-05-12 Arsenii Kuznetsov , Pavel Shvechikov , Alexander Grishin , Dmitry Vetrov

Several approaches to testing the hypothesis that two histograms are drawn from the same distribution are investigated. We note that single-sample continuous distribution tests may be adapted to this two-sample grouped data situation. The…

Data Analysis, Statistics and Probability · Physics 2008-04-03 Frank C. Porter

We give highly efficient algorithms, and almost matching lower bounds, for a range of basic statistical problems that involve testing and estimating the L_1 distance between two k-modal distributions $p$ and $q$ over the discrete domain…

Data Structures and Algorithms · Computer Science 2011-12-26 Constantinos Daskalakis , Ilias Diakonikolas , Rocco A. Servedio , Gregory Valiant , Paul Valiant

To simulate bosons on a qubit- or qudit-based quantum computer, one has to regularize the theory by truncating infinite-dimensional local Hilbert spaces to finite dimensions. In the search for practical quantum applications, it is important…

Quantum Physics · Physics 2024-04-03 Masanori Hanada , Junyu Liu , Enrico Rinaldi , Masaki Tezuka

The notion of testing for equivalence of two treatments is widely used in clinical trials, pharmaceutical experiments,bioequivalence and quality control. It is essentially approached within the intersection-union (IU) principle. According…

Applications · Statistics 2018-02-07 R. Arboretti , E. Carrozzo , F. Pesarin , L. Salmaso

Necessary and sufficient conditions of uniform consistency are explored. A hypothesis is simple. Nonparametric sets of alternatives are bounded convex sets in $\mathbb{L}_p$, $p >1$ with "small" balls deleted. The "small" balls have the…

Statistics Theory · Mathematics 2024-03-07 Mikhail Ermakov

Consider a fixed universe of $N=2^n$ elements and the uniform distribution over elements of some subset of size $K$. Given samples from this distribution, the task of complement sampling is to provide a sample from the complementary subset.…

Quantum Physics · Physics 2026-02-02 Marcello Benedetti , Harry Buhrman , Jordi Weggemans