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Hierarchical models represent a challenging setting for inference algorithms. MCMC methods struggle to scale to large models with many local variables and observations, and variational inference (VI) may fail to provide accurate…

Machine Learning · Computer Science 2022-07-27 Tomas Geffner , Justin Domke

This work develops new results for stochastic approximation algorithms. The emphases are on treating algorithms and limits with discontinuities. The main ingredients include the use of differential inclusions, set-valued analysis, and…

Probability · Mathematics 2021-08-31 Nhu Nguyen , George Yin

This work presents set-membership adaptive algorithms based on time-varying error bounds for CDMA interference suppression. We introduce a modified family of set-membership adaptive algorithms for parameter estimation with time-varying…

Information Theory · Computer Science 2013-01-03 Rodrigo C. de Lamare , Paulo S. R. Diniz

We present a novel end-to-end deep learning-based adaptation control algorithm for frequency-domain adaptive system identification. The proposed method exploits a deep neural network to map observed signal features to corresponding…

Audio and Speech Processing · Electrical Eng. & Systems 2022-03-07 Thomas Haubner , Andreas Brendel , Walter Kellermann

Many real-world systems modeled using differential equations involve unknown or uncertain parameters. Standard approaches to address parameter estimation inverse problems in this setting typically focus on estimating constants; yet some…

Dynamical Systems · Mathematics 2024-03-25 Anna Fitzpatrick , Molly Folino , Andrea Arnold

The control of ensembles of dynamical systems is an intriguing and challenging problem, arising for example in quantum control. We initiate the investigation of optimal control of ensembles of discrete-time systems, focusing on minimising…

Optimization and Control · Mathematics 2025-11-07 Christian Fiedler , Alessandro Scagliotti

By projecting onto complex optical mode profiles, it is possible to estimate arbitrarily small separations between objects with quantum-limited precision, free of uncertainty arising from overlapping intensity profiles. Here we extend these…

In the setting of additive regression model for continuous time process, we establish the optimal uniform convergence rates and optimal asymptotic quadratic error of additive regression. To build our estimate, we use the marginal…

Statistics Theory · Mathematics 2007-06-11 Mohammed Debbarh , Bertrand Maillot

Time-frequency (TF) representations of time series are intrinsically subject to the boundary effects. As a result, the structures of signals that are highlighted by the representations are garbled when approaching the boundaries of the TF…

Signal Processing · Electrical Eng. & Systems 2021-02-24 Adrien Meynard , Hau-Tieng Wu

Analytic continuation of imaginary time or frequency data to the real axis is a crucial step in extracting dynamical properties from quantum Monte Carlo simulations. The average spectrum method provides an elegant solution by integrating…

Computational Physics · Physics 2020-07-15 Khaldoon Ghanem , Erik Koch

This paper provides statistical guarantees on the accuracy of dynamical models learned from dependent data sequences. Specifically, we develop uniform error bounds that apply to quantized models and imperfect optimization algorithms…

Machine Learning · Computer Science 2026-02-18 Abdelkader Metakalard , Fabien Lauer , Kevin Colin , Marion Gilson

In this paper, we propose two discontinuous dynamical systems in continuous time with guaranteed prescribed finite-time local convergence to strict local minima of a given cost function. Our approach consists of exploiting a Lyapunov-based…

Optimization and Control · Mathematics 2019-12-19 Orlando Romero , Mouhacine Benosman

This paper proposes a new method, in the frequency domain, to define absorbing boundary conditions for general two-dimensional problems. The main feature of the method is that it can obtain boundary conditions from the discretized equations…

Classical Physics · Physics 2015-05-14 Denis Duhamel , Tien-Minh Nguyen

Families of regimes for discrete control systems are studied possessing a special quasi-controllability property that is similar to the Kalman controllability property. A new approach is proposed to estimate the amplitudes of transient…

Dynamical Systems · Mathematics 2009-08-31 V. Kozyakin , A. Pokrovskii

The paper is devoted to the study of a new class of optimal control problems governed by discontinuous constrained differential inclusions of the sweeping type with involving the duration of the dynamic process into optimization. We develop…

Optimization and Control · Mathematics 2023-10-18 Giovanni Colombo , Boris S. Mordukhovich , Dao Nguyen , Trang Nguyen

We consider the problem of bounding large deviations for non-i.i.d. random variables that are allowed to have arbitrary dependencies. Previous works typically assumed a specific dependence structure, namely the existence of independent…

Probability · Mathematics 2018-11-06 Christoph H. Lampert , Liva Ralaivola , Alexander Zimin

This paper extends the forward-backward consistency index, originally introduced in Koopman modeling of systems without input, to the setting of control systems, providing a closed-form computable measure of accuracy for data-driven models…

Optimization and Control · Mathematics 2026-04-07 Masih Haseli , Jorge Cortés , Joel W. Burdick

This paper is concerned with the numerical implementation of a formula in the enclosure method as applied to a prototype inverse initial boundary value problem for thermal imaging in a one-space dimension. A precise error estimate of the…

Numerical Analysis · Mathematics 2015-12-02 Masaru Ikehata , Kiwoon Kwon

We provide bounds on the error between dynamics of an infinite dimensional bilinear Schr\"odinger equation and of its finite dimensional Galerkin approximations. Standard averaging methods are used on the finite dimensional approximations…

Optimization and Control · Mathematics 2015-03-19 Nabile Boussaïd , Marco Caponigro , Thomas Chambrion

We describe a framework in which is possible to develop and implement algorithms for the approximation of invariant measures of dynamical systems with a given bound on the error of the approximation. Our approach is based on a general…

Dynamical Systems · Mathematics 2017-10-05 Stefano Galatolo , Isaia Nisoli