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We present a unified large system analysis of linear receivers for a class of random matrix channels. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver,…

Information Theory · Computer Science 2009-09-29 Matthew J. M. Peacock , Iain B. Collings , Michael L. Honig

Convolutional neural networks have many hyperparameters such as the filter size, number of filters, and pooling size, which require manual tuning. Though deep stacked structures are able to create multi-scale and hierarchical…

Computer Vision and Pattern Recognition · Computer Science 2018-03-02 Ilker Cam , F. Boray Tek

We consider the joint estimation of change point locations and the sparsity pattern of the variance covariance matrix, which is assumed to evolve in a piecewise constant manner. By applying Group Fused LASSO and LASSO penalties to the…

Methodology · Statistics 2026-05-14 Ying Lin , Benjamin Poignard

A new Lp-norm constraint least mean square (Lp-LMS) algorithm with new strategy of varying p is presented, which is applied to system identification in this letter. The parameter p is iteratively adjusted by the gradient method applied to…

Systems and Control · Computer Science 2016-03-31 Yong Feng , Fei Chen , Jiasong Wu

In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current lasso model, in the sequence of models visited along the lasso solution path. We propose a simple test statistic…

Statistics Theory · Mathematics 2014-05-27 Richard Lockhart , Jonathan Taylor , Ryan J. Tibshirani , Robert Tibshirani

This paper studies the fluctuations of the signal-to-noise ratio (SNR) of minimum variance distorsionless response (MVDR) filters implementing diagonal loading in the estimation of the covariance matrix. Previous results in the signal…

Information Theory · Computer Science 2015-06-05 Francisco Rubio , Xavier Mestre , Walid Hachem

We develop a recursive least square (RLS) type algorithm with a minimax concave penalty (MCP) for adaptive identification of a sparse tap-weight vector that represents a communication channel. The proposed algorithm recursively yields its…

Signal Processing · Electrical Eng. & Systems 2023-04-03 Bowen Li , Suya Wu , Erin E. Tripp , Ali Pezeshki , Vahid Tarokh

We show that the two-stage adaptive Lasso procedure (Zou, 2006) is consistent for high-dimensional model selection in linear and Gaussian graphical models. Our conditions for consistency cover more general situations than those accomplished…

Statistics Theory · Mathematics 2009-03-17 Shuheng Zhou , Sara van de Geer , Peter Bühlmann

A general representation of the quaternion gradients presented in the literature is proposed, and an universal update equation for QLMS-like algorithms is obtained. The general update law is used to study the convergence of widely linear…

Optimization and Control · Mathematics 2014-10-13 Fernando G. Almeida Neto , Vítor H. Nascimento

An accelerated class of adaptive scheme of iterative thresholding algorithms is studied analytically and empirically. They are based on the feedback mechanism of the null space tuning techniques (NST+HT+FB). The main contribution of this…

Information Theory · Computer Science 2020-05-15 Ningning Han , Shidong Li , Zhanjie Song

In this paper we analyze the convergence of a family of robust Kalman filters. For each filter of this family the model uncertainty is tuned according to the so called tolerance parameter. Assuming that the corresponding state-space model…

Optimization and Control · Mathematics 2017-05-16 Mattia Zorzi

Positive-valued signal data is common in many biological and medical applications, where the data are often generated from imaging techniques such as mass spectrometry. In such a setting, the relative intensities of the raw features are…

Methodology · Statistics 2021-04-15 Stephen Bates , Robert Tibshirani

State estimation that combines observational data with mathematical models is central to many applications and is commonly addressed through filtering methods, such as ensemble Kalman filters. In this article, we examine the signal-tracking…

Numerical Analysis · Mathematics 2025-09-08 Nazanin Abedini , Jana de Wiljes , Svetlana Dubinkina

In this paper, an adaptive observer is proposed for multi-input multi-output (MIMO) discrete-time linear time-invariant (LTI) systems. Unlike existing MIMO adaptive observer designs, the proposed approach is applicable to LTI systems in…

Systems and Control · Electrical Eng. & Systems 2024-01-31 Anchita Dey , Shubhendu Bhasin

In this work we explore the fundamental structure-adaptiveness of state of the art randomized first order algorithms on regularized empirical risk minimization tasks, where the solution has intrinsic low-dimensional structure (such as…

Optimization and Control · Mathematics 2017-12-13 Junqi Tang , Francis Bach , Mohammad Golbabaee , Mike Davies

In this report, we propose a new adaptive time filter algorithm for the unsteady Stokes/Darcy model. First we present a first order ${\theta}$-scheme with the variable time step which is one parameter family of Linear Multi-step methods and…

Numerical Analysis · Mathematics 2022-08-29 Yi Qin , Yang Wang , Yi Li , Jian Li

We study the asymptotic properties of the adaptive Lasso in cointegration regressions in the case where all covariates are weakly exogenous. We assume the number of candidate I(1) variables is sub-linear with respect to the sample size (but…

Methodology · Statistics 2011-10-11 Eduardo F. Mendes

We propose an adaptive accelerated smoothing technique for a nonsmooth convex optimization problem where the smoothing update rule is coupled with the momentum parameter. We also extend the setting to the case where the objective function…

Optimization and Control · Mathematics 2026-04-21 Reza Rahimi Baghbadorani , Sergio Grammatico , Peyman Mohajerin Esfahani

This paper considers the problem of output feedback control for non-square multi-input multi-output systems with arbitrary relative degree. The proposed controller, based on the L1 adaptive control architecture, is designed using the right…

Optimization and Control · Mathematics 2024-12-20 Hanmin Lee , Venanzio Cichella , Naira Hovakimyan

We propose a theoretical framework for an adaptive learning rate policy for the Mean Absolute Error loss function and Quantile loss function and evaluate its effectiveness for regression tasks. The framework is based on the theory of…

Machine Learning · Computer Science 2020-06-25 Snehanshu Saha , Tejas Prashanth , Suraj Aralihalli , Sumedh Basarkod , T. S. B Sudarshan , Soma S Dhavala
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