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We consider linear models where $d$ potential causes $X_1,...,X_d$ are correlated with one target quantity $Y$ and propose a method to infer whether the association is causal or whether it is an artifact caused by overfitting or hidden…

Machine Learning · Statistics 2018-03-05 Dominik Janzing , Bernhard Schoelkopf

In this paper, a class of convex feasibility problems (CFPs) are studied for multi-agent systems through local interactions. The objective is to search a feasible solution to the convex inequalities with some set constraints in a…

Systems and Control · Computer Science 2016-12-16 Kaihong Lu , Gangshan Jing , Long Wang

We study parameter identifiability of directed Gaussian graphical models with one latent variable. In the scenario we consider, the latent variable is a confounder that forms a source node of the graph and is a parent to all other nodes,…

Statistics Theory · Mathematics 2015-05-08 Dennis Leung , Mathias Drton , Hisayuki Hara

For a finite collection $\mathbf A=(A_i)_{i\in I}$ of locally closed sets in $\mathbb R^n$, $n\geqslant3$, with the sign $\pm1$ prescribed such that the oppositely charged plates are mutually disjoint, we consider the minimum energy problem…

Classical Analysis and ODEs · Mathematics 2018-02-21 Bent Fuglede , Natalia Zorii

We study the connection between probability distributions satisfying certain conditional independence (CI) constraints, and point and line arrangements in incidence geometry. To a family of CI statements, we associate a polynomial ideal…

Commutative Algebra · Mathematics 2021-04-01 Oliver Clarke , Fatemeh Mohammadi , Harshit J. Motwani

We consider general Gaussian latent tree models in which the observed variables are not restricted to be leaves of the tree. Extending related recent work, we give a full semi-algebraic description of the set of covariance matrices of any…

Statistics Theory · Mathematics 2018-10-30 Dennis Leung , Mathias Drton

Estimating causal quantities traditionally relies on bespoke estimators tailored to specific assumptions. Recently proposed Causal Foundation Models (CFMs) promise a more unified approach by amortising causal discovery and inference in a…

The input in the Minimum-Cost Constraint Satisfaction Problem (MinCSP) over the Point Algebra contains a set of variables, a collection of constraints of the form $x < y$, $x = y$, $x \leq y$ and $x \neq y$, and a budget $k$. The goal is to…

Data Structures and Algorithms · Computer Science 2024-05-08 George Osipov , Marcin Pilipczuk , Magnus Wahlström

Wheeler nondeterministic finite automata (WNFAs) were introduced as a generalization of prefix sorting from strings to labeled graphs. WNFAs admit optimal solutions to classic hard problems on labeled graphs and languages. The problem of…

Data Structures and Algorithms · Computer Science 2023-12-19 Ruben Becker , Manuel Cáceres , Davide Cenzato , Sung-Hwan Kim , Bojana Kodric , Francisco Olivares , Nicola Prezza

We prove that, for any measurable phase space subset $\Omega\subset\mathbb{R}^{2d}$ with $0<|\Omega|<\infty$ and any $1\le p < \infty$, the nonlinear concentration problem $$ \sup_{f \in…

Classical Analysis and ODEs · Mathematics 2026-05-26 Federico Stra , Erling A. T. Svela , S. Ivan Trapasso

The data drawn from biological, economic, and social systems are often confounded due to the presence of unmeasured variables. Prior work in causal discovery has focused on discrete search procedures for selecting acyclic directed mixed…

Machine Learning · Computer Science 2021-02-26 Rohit Bhattacharya , Tushar Nagarajan , Daniel Malinsky , Ilya Shpitser

We pose the fine-grained hardness hypothesis that the textbook algorithm for the NFA Acceptance problem is optimal up to subpolynomial factors, even for dense NFAs and fixed alphabets. We show that this barrier appears in many variations…

Computational Complexity · Computer Science 2024-10-09 Karl Bringmann , Allan Grønlund , Marvin Künnemann , Kasper Green Larsen

A common approach to analyze a covariate-sample count matrix, an element of which represents how many times a covariate appears in a sample, is to factorize it under the Poisson likelihood. We show its limitation in capturing the tendency…

Methodology · Statistics 2017-10-06 Mingyuan Zhou

In the traditional Katz-Vafa method, matter representations are determined by decomposing the adjoint representation of a parent simple Lie algebra $\mathfrak{m}$ as the direct sum of irreducible representations of a semisimple subalgebra…

High Energy Physics - Theory · Physics 2020-12-25 Mboyo Esole , Monica Jinwoo Kang

Estimating high-dimensional covariance matrices is a key task across many fields. This paper explores the theoretical limits of distributed covariance estimation in a feature-split setting, where communication between agents is constrained.…

Machine Learning · Statistics 2025-07-24 Mohammad Reza Rahmani , Mohammad Hossein Yassaee , Mohammad Reza Aref

We study the covariance property of quadratic time-frequency distributions with respect to the action of the extended symplectic group. We show how covariance is related, and in fact in competition, with the possibility of damping the…

Functional Analysis · Mathematics 2018-03-23 Elena Cordero , Maurice de Gosson , Monika Doerfler , Fabio Nicola

We study a version of the randomized Kaczmarz algorithm for solving systems of linear equations where the iterates are confined to the solution space of a selected subsystem. We show that the subspace constraint leads to an accelerated…

Numerical Analysis · Mathematics 2024-06-11 Jackie Lok , Elizaveta Rebrova

This paper has two primary objectives. First, we investigate fundamental qualitative properties of the generalized multi-source Weber problem formulated using the Minkowski gauge function. This includes proving the existence of global…

Optimization and Control · Mathematics 2024-09-23 Vo Si Trong Long , Nguyen Mau Nam , Tuyen Tran , Nguyen Thi Thu Van

We consider the problem of extracting a common structure from multiple tensor datasets. For this purpose, we propose multilinear common component analysis (MCCA) based on Kronecker products of mode-wise covariance matrices. MCCA constructs…

Machine Learning · Statistics 2020-11-23 Kohei Yoshikawa , Shuichi Kawano

Multi-omics data present significant challenges for statistical inference due to the complex interdependencies among biological layers. In this paper, we introduce a novel Multi-Omics Factor-Adjusted Cox (MOFA-Cox) model for analyzing…

Methodology · Statistics 2025-10-07 Heyuan Zhang , Meiling Hao , Lianqiang Qu , Liuquan Sun