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Denoising diffusions sample from a probability distribution $\mu$ in $\mathbb{R}^d$ by constructing a stochastic process $({\hat{\boldsymbol x}}_t:t\ge 0)$ in $\mathbb{R}^d$ such that ${\hat{\boldsymbol x}}_0$ is easy to sample, but the…

Machine Learning · Statistics 2026-04-09 Andrea Montanari , Viet Vu

We give an algorithm A which assigns probabilities to logical sentences. For any simple infinite sequence of sentences whose truth-values appear indistinguishable from a biased coin that outputs "true" with probability p, we have that the…

Machine Learning · Computer Science 2015-10-13 Scott Garrabrant , Siddharth Bhaskar , Abram Demski , Joanna Garrabrant , George Koleszarik , Evan Lloyd

A systematic study of the probability distribution of superimposed random codes is presented through the use of generating functions. Special attention is paid to the cases of either uniformly distributed but not necessarily independent or…

Databases · Computer Science 2008-06-19 Bernd Günther

In this paper we discuss the question how to bound supremum of a stochastic process with the index set of a product type. There is a tempting idea to approach the question by the analysis of the process on each of the marginal index spaces…

Probability · Mathematics 2016-02-01 Witold Bednorz

We consider the recovery of real-valued bandlimited functions from the absolute values of their samples, possibly spaced nonuniformly. We show that such a reconstruction is always possible if the function is sampled at more than twice its…

Numerical Analysis · Mathematics 2012-01-17 Gaurav Thakur

Bayesian learning in undirected graphical models|computing posterior distributions over parameters and predictive quantities is exceptionally difficult. We conjecture that for general undirected models, there are no tractable MCMC (Markov…

Machine Learning · Computer Science 2012-07-19 Iain Murray , Zoubin Ghahramani

Nature and our world have a bias! Roughly $30\%$ of the time the number $1$ occurs as the leading digit in many datasets base $10$. This phenomenon is known as Benford's law and it arrises in diverse fields such as the stock market,…

Probability · Mathematics 2023-08-16 Irfan Durmić , Steven J. Miller

We study the problem of estimating the value of a known smooth function $f$ at an unknown point $\boldsymbol{\mu} \in \mathbb{R}^n$, where each component $\mu_i$ can be sampled via a noisy oracle. Sampling more frequently components of…

Machine Learning · Computer Science 2022-03-22 Tavor Z. Baharav , Gary Cheng , Mert Pilanci , David Tse

This article summarises the theory of several bounded functional calculi for unbounded operators that have recently been discovered. The extend the Hille--Phillips calculus for (negative) generators $A$ of certain bounded $C_0$-semigroups,…

Functional Analysis · Mathematics 2022-02-08 Charles Batty , Alexander Gomilko , Yuri Tomilov

In this paper we introduce a new family of Bernstein-type exponential polynomials on the hypercube $[0, 1]^d$ and study their approximation properties. Such operators fix a multidimensional version of the exponential function and its…

Classical Analysis and ODEs · Mathematics 2024-05-28 Laura Angeloni , Danilo Costarelli , Chiara Darielli

We construct a general framework for deriving error bounds for conic feasibility problems. In particular, our approach allows one to work with cones that fail to be amenable or even to have computable projections, two previously challenging…

Optimization and Control · Mathematics 2022-10-17 Scott B. Lindstrom , Bruno F. Lourenço , Ting Kei Pong

Quantum circuits generating probability distributions has applications in several areas. Areas like finance require quantum circuits that can generate distributions that mimic some given data pattern. Hamiltonian simulations require…

Quantum Physics · Physics 2022-08-30 Kalyan Dasgupta , Binoy Paine

Suppose $f : [0,1]^2 \rightarrow \mathbb{R}$ is a $(c,\alpha)$-mixed H\"older function that we sample at $l$ points $X_1,\ldots,X_l$ chosen uniformly at random from the unit square. Let the location of these points and the function values…

Classical Analysis and ODEs · Mathematics 2022-03-03 Nicholas F. Marshall

Distribution testing deals with what information can be deduced about an unknown distribution over $\{1,\ldots,n\}$, where the algorithm is only allowed to obtain a relatively small number of independent samples from the distribution. In…

Computational Complexity · Computer Science 2016-09-23 Eldar Fischer , Oded Lachish , Yadu Vasudev

Multifractional Brownian motion is an extension of the well-known fractional Brownian motion where the Holder regularity is allowed to vary along the paths. In this paper, two kind of multi-parameter extensions of mBm are studied: one is…

Probability · Mathematics 2007-05-23 E. Herbin

We present a novel method for determining multi-fractal properties from experimental data. It is based on maximising the likelihood that the given finite data set comes from a particular set of parameters in a multi-parameter family of well…

chao-dyn · Physics 2009-10-28 A. J. Roberts , A. Cronin

We investigate certain spectral properties of the Bernoulli convolution measures on attractor sets arising from iterated function systems on the real line. In particular, we examine collections of orthogonal exponential functions in the…

Operator Algebras · Mathematics 2010-07-07 Palle Jorgensen , Keri Kornelson , Karen Shuman

The sum of $n$ {non-independent} Bernoulli random variables could be modeled in several different ways. One of these is the Multiplicative Binomial Distribution (MBD), introduced by Altham (1978) and revised by Lovison (1998). In this work,…

Statistics Theory · Mathematics 2018-02-26 Francesca Fortunato

Combinatorics, like computer science, often has to deal with large objects of unspecified (or unusable) structure. One powerful way to deal with such an arbitrary object is to decompose it into more usable components. In particular, it has…

Combinatorics · Mathematics 2011-11-10 Terence Tao

Using techniques from Poisson approximation, we prove explicit error bounds on the number of permutations that avoid any pattern. Most generally, we bound the total variation distance between the joint distribution of pattern occurrences…

Combinatorics · Mathematics 2023-06-22 Harry Crane , Stephen DeSalvo
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