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Semiautomata form a rich class of sequence-processing algorithms with applications in natural language processing, robotics, computational biology, and data mining. We establish the first Statistical Query hardness result for semiautomata…

Machine Learning · Computer Science 2025-10-07 George Giapitzakis , Kimon Fountoulakis , Eshaan Nichani , Jason D. Lee

In this chapter we report on the measurements of the overlap distribution of the replica symmetry breaking solution in complex disordered systems. After a general introduction to the problem of the experimental validation of the Parisi…

Disordered Systems and Neural Networks · Physics 2022-09-14 Claudio Conti , Neda Ghofraniha , Luca Leuzzi , Giancarlo Ruocco

This paper investigates the computational complexity of sparse label propagation which has been proposed recently for processing network structured data. Sparse label propagation amounts to a convex optimization problem and might be…

Machine Learning · Statistics 2018-05-30 Alexander Jung

By using stochastic analysis, two probability versions of Li-Yau type inequalities are established for diffusion semigroups on a manifold possibly with (non-convex) boundary. The inequalities are explicitly given by the Bakry-Emery…

Probability · Mathematics 2024-11-07 Feng-Yu Wang , Li-Juan Cheng

Dispersion is a fundamental concept in statistics, yet standard approaches - especially via stochastic orders - face limitations in the discrete setting. In particular, the classical dispersive order, well-established for continuous…

Methodology · Statistics 2025-11-11 Andreas Eberl , Bernhard Klar , Alfonso Suárez-Llorens

This paper introduces and reviews some of the principles and methods used in Bayesian reliability. It specifically discusses methods used in the analysis of success/no-success data and then reminds the reader of a simple Monte Carlo…

Methodology · Statistics 2024-06-10 Carsten H. Botts

Data complexity is an important concept in the natural sciences and related areas, but lacks a rigorous and computable definition. In this paper, we focus on a particular sense of complexity that is high if the data is structured in a way…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Louis Mahon

Robustness analysis is an emerging field in the domain of uncertainty quantification. It consists of analysing the response of a computer model with uncertain inputs to the perturbation of one or several of its input distributions. Thus, a…

Statistics Theory · Mathematics 2020-12-16 Clement Gauchy , Jerome Stenger , Roman Sueur , Bertrand Iooss

We review the methods of constructing confidence intervals that account for a priori information about one-sided constraints on the parameter being estimated. We show that the so-called method of sensitivity limit yields a correct solution…

Data Analysis, Statistics and Probability · Physics 2015-05-20 A. V. Lokhov , F. V. Tkachov

Given a countable set X (usually taken to be the natural numbers or integers), an infinite permutation, \pi, of X is a linear ordering of X. This paper investigates the combinatorial complexity of infinite permutations on the natural…

Discrete Mathematics · Computer Science 2011-08-19 Steven Widmer

This work presents a Fourier analysis framework for the non-interactive source simulation (NISS) problem. Two distributed agents observe a pair of sequences $X^d$ and $Y^d$ drawn according to a joint distribution $P_{X^dY^d}$. The agents…

Information Theory · Computer Science 2024-03-05 Hojat Allah Salehi , Farhad Shirani

Composable inductive programming as implemented in the Zoea programming language is a simple declarative approach to software development. At the language level it is evident that Zoea is significantly simpler than all mainstream languages.…

Programming Languages · Computer Science 2020-05-19 Edward McDaid , Sarah McDaid

We consider the learning and communication complexity of subsequence containment. In the learning problem, we seek to learn a classifier that positively labels a binary string $x$ if it contains a fixed binary string $y$ as a subsequence.…

Discrete Mathematics · Computer Science 2023-01-23 Mason DiCicco , Daniel Reichman

For large clause-to-variable ratio, typical K-SAT instances drawn from the uniform distribution have no solution. We argue, based on statistical mechanics calculations using the replica and cavity methods, that rare satisfiable instances…

Computational Complexity · Computer Science 2015-06-25 Fabrizio Altarelli , Remi Monasson , Francesco Zamponi

In problems of mathematical physics, to study the structures of spaces using the Cayley-Klein models in theoretical calculations, the use of generalized complex numbers is required. In the case of computational experiments, such tasks…

Mathematical Software · Computer Science 2020-07-21 Migran N. Gevorkyan , Anna V. Korolkova , Dmitry S. Kulyabov

Bayesian inference for models with intractable likelihood functions represents a challenging suite of problems in modern statistics. In this work we analyse the Conway-Maxwell-Poisson (COM-Poisson) distribution, a two parameter…

Computation · Statistics 2020-07-13 Alan Benson , Nial Friel

How do two distributions of texts differ? Humans are slow at answering this, since discovering patterns might require tediously reading through hundreds of samples. We propose to automatically summarize the differences by "learning a…

Computation and Language · Computer Science 2022-05-19 Ruiqi Zhong , Charlie Snell , Dan Klein , Jacob Steinhardt

Student experiences and empirical studies report that "black box" AI text detectors produce high false positive rates with disproportionate errors against certain student populations, yet typically theoretical analyses model detection as a…

Computers and Society · Computer Science 2026-03-24 Nathan Garland

While the standard unweighted Voronoi diagram in the plane has linear worst-case complexity, many of its natural generalizations do not. This paper considers two such previously studied generalizations, namely multiplicative and semi…

Computational Geometry · Computer Science 2020-04-21 Chenglin Fan , Benjamin Raichel

We consider predictions of the random number and the magnitude of each iid component in a random sum based on its distributional structure, where only a total value of the sum is available and where iid random components are non-negative.…

Probability · Mathematics 2015-07-13 Muneya Matsui