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Recent work has shown that probabilistic models based on pairwise interactions-in the simplest case, the Ising model-provide surprisingly accurate descriptions of experiments on real biological networks ranging from neurons to genes.…

Quantitative Methods · Quantitative Biology 2007-12-18 Tamara Broderick , Miroslav Dudik , Gasper Tkacik , Robert E. Schapire , William Bialek

In a Hilbert framework, we consider an inertial Tikhonov regularized dynamical system governed by a maximally comonotone operator, where the damping coefficient is proportional to the square root of the Tikhonov regularization parameter.…

Optimization and Control · Mathematics 2024-12-02 Zeng-Zhen Tan , Rong HU , Ya-Ping Fang

Regularized kernel methods such as support vector machines (SVM) and support vector regression (SVR) constitute a broad and flexible class of methods which are theoretically well investigated and commonly used in nonparametric…

Methodology · Statistics 2013-05-07 Robert Hable

This paper considers large-scale linear ill-posed inverse problems whose solutions can be represented as sums of smooth and piecewise constant components. To solve such problems we consider regularizers consisting of two terms that must be…

Numerical Analysis · Mathematics 2022-06-30 Ali Gholami , Silvia Gazzola

We consider Tikhonov regularization of control-constrained optimal control problems. We present new a-priori estimates for the regularization error assuming measure and source-measure conditions. In the special case of bang-bang solutions,…

Optimization and Control · Mathematics 2017-12-08 Nikolaus von Daniels

The inverse Ising problem seeks to reconstruct the parameters of an Ising Hamiltonian on the basis of spin configurations sampled from the Boltzmann measure. Over the last decade, many applications of the inverse Ising problem have arisen,…

Disordered Systems and Neural Networks · Physics 2017-09-13 Johannes Berg

We deal with the shape reconstruction of inclusions in elastic bodies. For solving this inverse problem in practice, data fitting functionals are used. Those work better than the rigorous monotonicity methods from [5], but have no…

Numerical Analysis · Mathematics 2022-12-13 Sarah Eberle , Bastian Harrach

A numerical algorithm for studying strongly correlated electron systems is proposed. The groundstate wavefunction is projected out after numerical renormalization procedure in the path integral formalism. The wavefunction is expressed from…

Strongly Correlated Electrons · Physics 2007-05-23 Masatoshi Imada , Tsuyoshi Kashima

The Arnoldi-Tikhonov method is a well-established regularization technique for solving large-scale ill-posed linear inverse problems. This method leverages the Arnoldi decomposition to reduce computational complexity by projecting the…

Numerical Analysis · Mathematics 2025-06-02 Davide Bianchi , Marco Donatelli , Davide Furchì , Lothar Reichel

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an…

Statistics Theory · Mathematics 2022-06-28 Alessia Caponera , Julien Fageot , Matthieu Simeoni , Victor M. Panaretos

In this paper we present a comprehensive analysis of the coherence phenomenon of two coupled dissipative oscillators. The action of a classical driving field on one of the oscillators is also analyzed. Master equations are derived for both…

Quantum Physics · Physics 2007-05-23 M. A. de Ponte , M. C. de Oliveira , M. H. Y. Moussa

We study incremental stability and convergence of switched (bimodal) Filippov systems via contraction analysis. In particular, by using results on regularization of switched dynamical systems, we derive sufficient conditions for convergence…

Systems and Control · Computer Science 2020-03-18 Mario di Bernardo , Davide Fiore , S. John Hogan

We implement the normal ordering technique to study the quantum dissipation of a single mode harmonic oscillator system. The dynamic evolution of the system is investigated for a reasonable initial state by solving the Schr\"{o}dinger…

Quantum Physics · Physics 2018-01-17 G. R. Jin , D. L. Zhou , Yu-xi Liu , X. X. Yi , C. P. Sun

The Tikhonov-Phillips method is widely used for regularizing ill-posed inverse problems mainly due to the simplicity of its formulation as an optimization problem. The use of different penalizers in the functionals associated to the…

Functional Analysis · Mathematics 2011-08-23 Gisela L. Mazzieri , Ruben D. Spies , Karina G. Temperini

We study multi-parameter regularization (multiple penalties) for solving linear inverse problems to promote simultaneously distinct features of the sought-for objects. We revisit a balancing principle for choosing regularization parameters…

Numerical Analysis · Mathematics 2013-06-26 Kazufumi Ito , Bangti Jin , Tomoya Takeuchi

Recovering microscopic couplings directly from data provides a route to solving the inverse problem in statistical field theories, one that complements the traditional-often computationally intractable-forward approach of predicting…

Statistical Mechanics · Physics 2025-11-24 Shreya Shukla , Abhijith Jayakumar , Andrey Y. Lokhov

The present paper explores the synchronization scenario of hyperchaotic time-delayed electronic oscillators coupled indirectly via a common environment. We show that depending upon the coupling parameters a hyperchaotic time-delayed system…

Chaotic Dynamics · Physics 2013-07-23 Tanmoy Banerjee , Debabrata Biswas

We review the theory of weakly coupled oscillators for smooth systems. We then examine situations where application of the standard theory falls short and illustrate how it can be extended. Specific examples are given to non-smooth systems…

Adaptation and Self-Organizing Systems · Physics 2020-06-14 Bard Ermentrout , Youngmin Park , Dan Wilson

In this paper, we investigate iterative methods that are based on sampling of the data for computing Tikhonov-regularized solutions. We focus on very large inverse problems where access to the entire data set is not possible all at once…

Numerical Analysis · Mathematics 2018-12-18 J. Tanner Slagel , Julianne Chung , Matthias Chung , David Kozak , Luis Tenorio

By introducing a shape manifold as a solution set to solve inverse obstacle scattering problems we allow the reconstruction of general, not necessarily star-shaped curves. The bending energy is used as a stabilizing term in Tikhonov…

Numerical Analysis · Mathematics 2020-01-08 Julian Eckhardt , Ralf Hiptmair , Thorsten Hohage , Henrik Schumacher , Max Wardetzky