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High-order tensor methods that employ Taylor-based local models (of degree $p\ge 3$) within adaptive regularization frameworks have been recently proposed for both convex and nonconvex optimization problems. They have been shown to have…

Optimization and Control · Mathematics 2024-04-19 Wenqi Zhu , Coralia Cartis

Consistent reconstruction is a method for producing an estimate $\widetilde{x} \in \mathbb{R}^d$ of a signal $x\in \mathbb{R}^d$ if one is given a collection of $N$ noisy linear measurements $q_n = \langle x, \varphi_n \rangle +…

Information Theory · Computer Science 2014-05-29 Alexander M. Powell , J. Tyler Whitehouse

Ambulatory blood pressure monitoring (ABPM) enables continuous measurement of blood pressure and heart rate over 24 hours and is increasingly used in clinical studies. However, ABPM data are often reduced to summary statistics, such as…

Methodology · Statistics 2025-07-17 Leyuan Qian , R. Nisha Aurora , Naresh M. Punjabi , Irina Gaynanova

We present the $\delta$-Synchronizer, which works in non-synchronous dynamic networks under minimal assumptions. Our model allows for arbitrary topological changes without any guarantee of eventual global or partial stabilization and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-30 Rida Bazzi , Cameron Bickley , Anya Chaturvedi , Andréa W. Richa , Peter Vargas

We consider stochastic convex optimization problems where the objective is an expectation over smooth functions. For this setting we suggest a novel gradient estimate that combines two recent mechanism that are related to notion of…

Machine Learning · Computer Science 2025-03-06 Tehila Dahan , Kfir Y. Levy

We study the problem of asymptotic consensus as it occurs in a wide range of applications in both man-made and natural systems. In particular, we study systems with directed communication graphs that may change over time. We recently…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-09 Bernadette Charron-Bost , Matthias Függer , Thomas Nowak

Recently, distributed dual averaging has received increasing attention due to its superiority in handling constraints and dynamic networks in multiagent optimization. However, all distributed dual averaging methods reported so far…

Optimization and Control · Mathematics 2020-03-20 Changxin Liu , Huiping Li , Yang Shi

Sparsity promoting norms are frequently used in high dimensional regression. A limitation of such Lasso-type estimators is that the optimal regularization parameter depends on the unknown noise level. Estimators such as the concomitant…

Machine Learning · Statistics 2020-09-04 Quentin Bertrand , Mathurin Massias , Alexandre Gramfort , Joseph Salmon

The moment conditions or estimating equations for instrumental variables quantile regression involve the discontinuous indicator function. We instead use smoothed estimating equations (SEE), with bandwidth $h$. We show that the mean squared…

Methodology · Statistics 2018-02-28 David M. Kaplan , Yixiao Sun

Anomaly detection in spatiotemporal data is a challenging problem encountered in a variety of applications, including video surveillance, medical imaging data, and urban traffic monitoring. Existing anomaly detection methods focus mainly on…

Machine Learning · Computer Science 2025-10-02 Rachita Mondal , Mert Indibi , Tapabrata Maiti , Selin Aviyente

Estimating position and orientation change of a mobile platform from two consecutive point clouds provided by a high-resolution sensor is a key problem in autonomous navigation. In particular, scan matching algorithms aim to find the…

Signal Processing · Electrical Eng. & Systems 2021-06-09 Rico Mendrzik , Florian Meyer

Motivated by understanding and analysis of large-scale machine learning under heavy-tailed gradient noise, we study decentralized optimization with gradient clipping, i.e., in which certain clipping operators are applied to the gradients or…

Optimization and Control · Mathematics 2024-11-12 Shuhua Yu , Dusan Jakovetic , Soummya Kar

This paper concerns the problem of recovering an unknown but structured signal $x \in R^n$ from $m$ quadratic measurements of the form $y_r=|<a_r,x>|^2$ for $r=1,2,...,m$. We focus on the under-determined setting where the number of…

Machine Learning · Computer Science 2017-02-22 Mahdi Soltanolkotabi

Measure synchronization is a well-known phenomenon in coupled classical Hamiltonian systems over last two decades. In this paper, synchronization for coupled Harper system is investigated in both classical and quantum contexts. The concept…

Quantum Physics · Physics 2020-02-19 Saikat Sur , Anupam Ghosh

In this paper, we develop an asymptotic expansion-regularization (AER) method for inverse source problems in two-dimensional nonlinear and nonstationary singularly perturbed partial differential equations (PDEs). The key idea of this…

Numerical Analysis · Mathematics 2022-10-14 Dmitrii Chaikovskii , Aleksei Liubavin , Ye Zhang

Analog layout synthesis requires some elements in the circuit netlist to be matched and placed symmetrically. However, the set of symmetries is very circuit-specific and a versatile algorithm, applicable to a broad variety of circuits, has…

Machine Learning · Computer Science 2020-10-02 Kishor Kunal , Jitesh Poojary , Tonmoy Dhar , Meghna Madhusudan , Ramesh Harjani , Sachin S. Sapatnekar

Generating wide-area digital surface models (DSMs) requires registering a large number of individual, and partially overlapped DSMs. This presents a challenging problem for a typical registration algorithm, since when a large number of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Ningli Xu , Rongjun Qin

Delay tomography has so far burdened source and receiver measurement nodes in a network with two requirements such as path establishment and clock synchronization between them. In this letter, we focus on the clock synchronization problem…

Networking and Internet Architecture · Computer Science 2014-02-24 Kensuke Nakanishi , Shinsuke Hara , Takahiro Matsuda , Kenichi Takizawa , Fumie Ono , Ryu Miura

This work considers the problem of finding a first-order stationary point of a non-convex function with potentially unbounded smoothness constant using a stochastic gradient oracle. We focus on the class of $(L_0,L_1)$-smooth functions…

Machine Learning · Statistics 2023-02-14 Matthew Faw , Litu Rout , Constantine Caramanis , Sanjay Shakkottai

In this paper we consider a dynamic computer simulator that produces a time-series response $y_t(x)$ over $L$ time points, for every given input parameter $x$. We propose a method for solving inverse problems, which refer to the finding of…

Methodology · Statistics 2020-12-15 Joseph Resch , Abhyuday Mandal , Pritam Ranjan
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