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Contraction theory for dynamical systems on Euclidean spaces is well-established. For contractive (resp. semi-contractive) systems, the distance (resp. semi-distance) between any two trajectories decreases exponentially fast. For partially…

Optimization and Control · Mathematics 2021-06-07 Pedro Cisneros-Velarde , Saber Jafarpour , Francesco Bullo

We present a general conceptual framework for self-organized criticality (SOC), based on the recognition that it is nothing but the expression, ''unfolded'' in a suitable parameter space, of an underlying {\em unstable} dynamical critical…

adap-org · Physics 2009-10-22 Didier Sornette , Anders Johansen , Ivan Dornic

We develop causality theory for upper semi-continuous distributions of cones over manifolds generalizing results from mathematical relativity in two directions: non-round cones and non-regular differentiability assumptions. We prove the…

General Relativity and Quantum Cosmology · Physics 2019-03-06 E. Minguzzi

To better understand the correlation between network topological features and the robustness of network controllability in a general setting, this paper suggests a practical approach to searching for optimal network topologies with given…

Systems and Control · Electrical Eng. & Systems 2020-09-02 Yang Lou , Lin Wang , Kim Fung Tsang , Guanrong Chen

Causal modeling has long been an attractive topic for many researchers and in recent decades there has seen a surge in theoretical development and discovery algorithms. Generally discovery algorithms can be divided into two approaches:…

Machine Learning · Statistics 2017-02-06 Ridho Rahmadi , Perry Groot , Marianne Heins , Hans Knoop , Tom Heskes

Positive semidefinite rank (PSD-rank) is a relatively new quantity with applications to combinatorial optimization and communication complexity. We first study several basic properties of PSD-rank, and then develop new techniques for…

Computational Complexity · Computer Science 2014-07-17 Troy Lee , Zhaohui Wei , Ronald de Wolf

The contemporary forestry preoccupation with non-declining even-flow during yield simulations detracts from more important questions about the constraints that should bind the end of a simulation. Whilst long simulations help to convey a…

Quantitative Methods · Quantitative Biology 2014-10-07 Jerome K. Vanclay

We address the problem of incremental sequence classification, where predictions are updated as new elements in the sequence are revealed. Drawing on temporal-difference learning from reinforcement learning, we identify a…

Approximate necessary optimality conditions in terms of Fr\'echet subgradients and normals for a rather general optimization problem with a potentially non-Lipschitzian objective function are established with the aid of Ekeland's…

Optimization and Control · Mathematics 2021-10-15 Alexander Y. Kruger , Patrick Mehlitz

The Sheaf-Theoretic Contextuality (STC) theory developed by Abramsky and colleagues is a very general account of whether multiply overlapping subsets of a set, each of which is endowed with certain "local'" structure, can be viewed as…

Quantum Physics · Physics 2023-04-11 Ehtibar N. Dzhafarov

This paper develops a novel approach to necessary optimality conditions for constrained variational problems defined in generally incomplete subspaces of absolutely continuous functions. Our approach involves reducing a variational problem…

Optimization and Control · Mathematics 2021-11-01 Ashkan Mohammadi , Boris Mordukhovich

In the present paper, a systematic study is made of quantitative semicontinuity (a.k.a. Lipschitzian) properties of certain multifunctions, which are defined as a solution map associated to a family of parameterized ``split" feasibility…

Optimization and Control · Mathematics 2026-04-01 Amos Uderzo

In-Context Learning (ICL) allows Large Language Models (LLMs) to adapt to new tasks with just a few examples, but their predictions often suffer from systematic biases, leading to unstable performance in classification. While calibration…

Machine Learning · Statistics 2026-03-05 Korel Gundem , Juncheng Dong , Dennis Zhang , Vahid Tarokh , Zhengling Qi

Partial calmness is a celebrated but restrictive property of bilevel optimization problems whose presence opens a way to the derivation of Karush--Kuhn--Tucker-type necessary optimality conditions in order to characterize local minimizers.…

Optimization and Control · Mathematics 2020-06-30 Patrick Mehlitz , Leonid I. Minchenko , Alain B. Zemkoho

One of the most ubiquitous problems in optimization is that of finding all the elements of a finite set at which a function $f$ attains its minimum (or maximum). When the codomain of $f$ is equipped with a total order, it is easy to…

Optimization and Control · Mathematics 2026-03-17 Patrik Jansson , Nicola Botta , Tim Richter

The efficacy of robust optimization spans a variety of settings with uncertainties bounded in predetermined sets. In many applications, uncertainties are affected by decisions and cannot be modeled with current frameworks. This paper takes…

Optimization and Control · Mathematics 2018-03-29 Omid Nohadani , Kartikey Sharma

In this paper, we are concerned with stationarity conditions and qualification conditions for optimization problems with disjunctive constraints. This class covers, among others, optimization problems with complementarity, vanishing, or…

Optimization and Control · Mathematics 2025-10-14 Isabella Käming , Patrick Mehlitz

We review some features of topology optimization with a lower bound on the critical load factor, as computed by linearized buckling analysis. The change of the optimized design, the competition between stiffness and stability requirements…

Numerical Analysis · Mathematics 2018-09-25 Federico Ferrari , Ole Sigmund

Two approaches to Lipschitz structures for any set are presented, studied and compared. The first approach is similar to the one proposed in Fraser, Jr. R. B., Axiom systems for Lipschitz structures, Fundamenta Mathematicae, (1970), where…

General Topology · Mathematics 2024-04-23 Tullio Valent

Statistical inference for non-stationary data is hindered by the failure of classical central limit theorems (CLTs), not least because there is no fixed Gaussian limit to converge to. To resolve this, we introduce relative weak convergence,…

Statistics Theory · Mathematics 2025-10-28 Nicolai Palm , Thomas Nagler