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In this paper, an efficient modified Newton type algorithm is proposed for nonlinear unconstrianed optimization problems. The modified Hessian is a convex combination of the identity matrix (for steepest descent algorithm) and the Hessian…

Optimization and Control · Mathematics 2015-10-09 Yaguang Yang

This paper investigates the convex optimization problem with general convex inequality constraints. To cope with this problem, a discrete-time algorithm, called augmented primal-dual gradient algorithm (Aug-PDG), is studied and analyzed. It…

Optimization and Control · Mathematics 2020-11-18 Min Meng , Xiuxian Li

In this paper we study algorithms to find a Gaussian approximation to a target measure defined on a Hilbert space of functions; the target measure itself is defined via its density with respect to a reference Gaussian measure. We employ the…

Numerical Analysis · Mathematics 2014-08-11 Frank J. Pinski , Gideon Simpson , Andrew M. Stuart , Hendrik Weber

This paper discusses the problem of adaptive estimation of a univariate object like the value of a regression function at a given point or a linear functional in a linear inverse problem. We consider an adaptive procedure originated from…

Statistics Theory · Mathematics 2009-08-26 Vladimir Spokoiny , Céline Vial

A three-point iterative method for solving scalar non-linear equations was selected and then adapted to solve systems of non-linear equations. Subsequently, by applying Taylor's theorem to functions of $\R^{n}$ in $\R^{n}$, it is shown that…

General Mathematics · Mathematics 2026-01-23 Carlos E. Cadenas R. , Yorman J. Mendoza N

Euler's elastica model has been extensively studied and applied to image processing tasks. However, due to the high nonlinearity and nonconvexity of the involved curvature term, conventional algorithms suffer from slow convergence and high…

Image and Video Processing · Electrical Eng. & Systems 2019-08-06 Yinghui Zhang , Xiaojuan Deng , Jun Zhang , Hongwei Li

We explore precision in a measurement process incorporating pure probe states, unitary dynamics and complete measurements via a simple formalism. The concept of `information complement' is introduced. It undermines measurement precision and…

Quantum Physics · Physics 2010-02-17 Gabriel A. Durkin

Optimizations premised on open-loop metrics such as Age of Information (AoI) indirectly enhance the system's decision-making utility. We therefore propose a novel closed-loop metric named Goal-oriented Tensor (GoT) to directly quantify the…

Information Theory · Computer Science 2023-07-04 Aimin Li , Shaohua Wu , Sumei Sun , Jie Cao

The doubly minimized Petz Renyi mutual information (PRMI) of order $\alpha$ is defined as the minimization of the Petz divergence of order $\alpha$ of a fixed bipartite quantum state $\rho_{AB}$ relative to any product state…

Quantum Physics · Physics 2025-07-08 Laura Burri

The concept of information has emerged as a language in its own right, bridging several disciplines that analyze natural phenomena and man-made systems. Integrated information has been introduced as a metric to quantify the amount of…

Neurons and Cognition · Quantitative Biology 2019-06-10 Alberto Hernández-Espinosa , Héctor Zenil , Narsis A. Kiani , Jesper Tegnér

We introduce three new nonlinear continuous data assimilation algorithms. These models are compared with the linear continuous data assimilation algorithm introduced by Azouani, Olson, and Titi (AOT). As a proof-of-concept for these models,…

Analysis of PDEs · Mathematics 2017-03-13 Adam Larios , Yuan Pei

In this work we present a new method for the estimation of Mutual Information (MI) between random variables. Our approach is based on an original interpretation of the Girsanov theorem, which allows us to use score-based diffusion models to…

Machine Learning · Computer Science 2024-05-16 Giulio Franzese , Mustapha Bounoua , Pietro Michiardi

We study lower bounds on the worst-case error of numerical integration in tensor product spaces. As reference we use the $N$-th minimal error of linear rules that use $N$ function values. The information complexity is the minimal number $N$…

Numerical Analysis · Mathematics 2024-04-29 Erich Novak , Friedrich Pillichshammer

We provide algorithms that guarantee regret $R_T(u)\le \tilde O(G\|u\|^3 + G(\|u\|+1)\sqrt{T})$ or $R_T(u)\le \tilde O(G\|u\|^3T^{1/3} + GT^{1/3}+ G\|u\|\sqrt{T})$ for online convex optimization with $G$-Lipschitz losses for any comparison…

Machine Learning · Statistics 2019-02-26 Ashok Cutkosky

The dynamic environment in the real world calls for the adaptive techniques for information filtering, namely to provide real-time responses to the changes of system data. Where many incremental algorithms are designed for this purpose,…

Information Retrieval · Computer Science 2009-11-26 Ci-Hang Jin , Jian-Guo Liu , Yi-Cheng Zhang , Tao Zhou

This paper presents an improved forward-backward splitting algorithm with two inertial parameters. It aims to find a point in the real Hilbert space at which the sum of a co-coercive operator and a maximal monotone operator vanishes. Under…

Machine Learning · Computer Science 2025-05-08 İrfan Işik , Ibrahim Karahan , Okan Erkaymaz

Here, we investigate the uncertainty of dynamical observables in classical systems manipulated by repeated measurements and feedback control; the precision should be enhanced in the presence of an external controller but limited by the…

Statistical Mechanics · Physics 2020-01-23 Tan Van Vu , Yoshihiko Hasegawa

The accuracy of the Arthurs-Kelly model of a simultaneous measurement of position and momentum is analysed using concepts developed by Braginsky and Khalili in the context of measurements of a single quantum observable. A distinction is…

Quantum Physics · Physics 2008-11-26 D. M. Appleby

This paper develops information geometric representations for nonlinear filters in continuous time. The posterior distribution associated with an abstract nonlinear filtering problem is shown to satisfy a stochastic differential equation on…

Probability · Mathematics 2015-07-28 Nigel J. Newton

In this paper, we investigate a second-order stochastic algorithm for solving large-scale binary classification problems. We propose to make use of a new hybrid stochastic Newton algorithm that includes two weighted components in the…

Computation · Statistics 2025-12-02 Bernard Bercu , Luis Fredes , Eméric Gbaguidi
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