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We consider the problem of learning causal networks with interventions, when each intervention is limited in size under Pearl's Structural Equation Model with independent errors (SEM-IE). The objective is to minimize the number of…

Artificial Intelligence · Computer Science 2015-11-03 Karthikeyan Shanmugam , Murat Kocaoglu , Alexandros G. Dimakis , Sriram Vishwanath

Point identification of causal effects requires strong assumptions that are unreasonable in many practical settings. However, informative bounds on these effects can often be derived under plausible assumptions. Even when these bounds are…

Methodology · Statistics 2024-04-18 Julien D. Laurendeau , Aaron L. Sarvet , Mats J. Stensrud

Estimating causal effects under interference, where the stable unit treatment value assumption is violated, is critical in fields such as regional and public economics. Much of the existing research on causal inference under interference…

Methodology · Statistics 2026-02-03 Akihiro Sato , Shonosuke Sugasawa

A modular or distributive lattice is `diamond-colored' if its order diagram edges are colored in such a way that, within any diamond of edges, parallel edges have the same color. Such lattices arise naturally in combinatorial representation…

Combinatorics · Mathematics 2022-05-10 Robert G. Donnelly

Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated…

Methodology · Statistics 2015-11-17 Ilya Shpitser , Eric Tchetgen Tchetgen

We propose a new approach to compute an interval over-approximation of the finite time reachable set for a large class of nonlinear systems. This approach relies on the notions of sensitivity matrices, which are the partial derivatives…

Systems and Control · Electrical Eng. & Systems 2021-04-19 Pierre-Jean Meyer , Murat Arcak

Adaptive cognition requires structured internal models of objects and their relations. Predictive neural networks are often proposed to learn such world models, but how these are instantiated and how they support prediction remain unclear.…

Machine Learning · Computer Science 2026-05-11 Linda Ariel Ventura , Victoria Bosch , Tim C Kietzmann , Sushrut Thorat

We study Markov Decision Processes (MDP) wherein states correspond to causal graphs that stochastically generate rewards. In this setup, the learner's goal is to identify atomic interventions that lead to high rewards by intervening on…

Machine Learning · Computer Science 2021-11-02 Rahul Madhavan , Aurghya Maiti , Gaurav Sinha , Siddharth Barman

The sensitivity analysis of biological system models can significantly contribute to identifying and explaining influences of internal or external changes on model and its elements. We propose here a comprehensive framework to study…

Molecular Networks · Quantitative Biology 2019-02-11 Gaoxiang Zhou , Kai-Wen Liang , Natasa Miskov-Zivanov

Sequential self-attention models usually rely on additive positional embeddings, which inject positional information into item representations at the input. In the absence of positional signals, the attention block is…

Information Retrieval · Computer Science 2026-02-25 Timur Nabiev , Evgeny Frolov

We introduce a framework for the design of finite element methods for two-dimensional moving boundary problems with prescribed boundary evolution that have arbitrarily high order of accuracy, both in space and in time. At the core of our…

Numerical Analysis · Mathematics 2015-06-19 Evan S. Gawlik , Adrian J. Lew

Bandit algorithms have become a reference solution for interactive recommendation. However, as such algorithms directly interact with users for improved recommendations, serious privacy concerns have been raised regarding its practical use.…

Machine Learning · Computer Science 2022-09-01 Huazheng Wang , David Zhao , Hongning Wang

We discuss how one calculates the coherent path integrals for locally interacting systems, where some inconsistencies with exact results have been reported previously. It is shown that the operator ordering subtlety that is hidden in the…

Quantum Physics · Physics 2017-10-25 Nobuhiko Taniguchi

A nonequilibrium system of locally interacting elements in a lattice with an absorbing order-disorder phase transition is studied under the effect of additional interacting fields. These fields are shown to produce interesting effects in…

Statistical Mechanics · Physics 2007-09-09 J. C. Gonzalez-Avella , V. M. Eguiluz , M. G. Cosenza , K. Klemm , J. L. Herrera , M. San Miguel

We investigate the dynamic behavior of lattices with disorder introduced through non-local network connections. Inspired by the Watts-Strogatz small-world model, we employ a single parameter to determine the probability of local connections…

Applied Physics · Physics 2022-07-27 Matheus I. N. Rosa , Massimo Ruzzene

Recent methodological research in causal inference has focused on effects of stochastic interventions, which assign treatment randomly, often according to subject-specific covariates. In this work, we demonstrate that the usual notion of…

Designing causal bandit algorithms depends on two central categories of assumptions: (i) the extent of information about the underlying causal graphs and (ii) the extent of information about interventional statistical models. There have…

Machine Learning · Statistics 2024-11-05 Zirui Yan , Ali Tajer

In the first part of this paper, we prove that, under some natural non-degeneracy assumptions, the Greedy Parabolic Target-Following Method, based on {\em universal tangent direction} has a favorable local behavior. In view of its global…

Optimization and Control · Mathematics 2024-12-20 Yurii Nesterov

In the present study, we propose a unique scheme to generate and control multiple flat bands in a decorated diamond chain by using a strain-induced proximity effect between the diagonal sites of each diamond plaquette. This is in complete…

Strongly Correlated Electrons · Physics 2025-12-11 K Shivanand Thakur , Vihodi Theuno , Amrita Mukherjee , Biplab Pal

We propose a new proximal, path-following framework for a class of constrained convex problems. We consider settings where the nonlinear---and possibly non-smooth---objective part is endowed with a proximity operator, and the constraint set…

Optimization and Control · Mathematics 2016-12-28 Quoc Tran-Dinh , Anastasios Kyrillidis , Volkan Cevher
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