Publications related to Ridge regression

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Volkan Cevher

This paper proposes a tradeoff between computational time, sample complexity, and statistical accuracy that applies to statistical estimators based on convex optimization. When we have a large amount of data, we can exploit excess samples to decrease stati ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Process Design and Optimization (MLS-S03): a Journey in Modeling, Optimization and Regression

Julien Léo Billeter

This lecture describes the following topics: • Preamble on Linear Algebra • Dynamic and Static Models • Solving Dynamic and Static Models • Solving Optimization Problems • Solving Regression Problems ...

2015

Total Variation Regularization of Shape Signals

Martin Kurt Storath

This paper introduces the concept of shape signals, i.e., series of shapes which have a natural temporal or spatial ordering, as well as a variational formulation for the regularization of these signals. The proposed formulation can be seen as the shape-va ...

IEEE2015

Towards Convenient Calibration for Cross-Ratio based Gaze Estimation

Jean-Philippe Thiran, Nuri Murat Arar, Hua Gao

Eye gaze movements are considered as a salient modality for human computer interaction applications. Recently, cross-ratio (CR) based eye tracking methods have attracted increasing interest because they provide remote gaze estimation using a single uncalib ...

2015

EMG-based learning approach for estimating wrist motion

Aude Billard, Silvestro Micera, Sahar El Khoury, Iason Batzianoulis

This paper proposes an EMG based learning approach for estimating the displacement along the 2-axes (abduction/adduction and flexion/extension) of the human wrist in real-time. The algorithm extracts features from the EMG electrodes on the upper and forear ...

2015

Isotropic Inverse-Problem Approach for Two-Dimensional Phase Unwrapping

Michaël Unser, Demetri Psaltis, Ulugbek Kamilov

We propose a new technique for two-dimensional phase unwrapping. The unwrapped phase is found as the solution of an inverse problem that consists in the minimization of an energy functional. The latter includes a weighted data fidelity term that favors spa ...

JOSA2015

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Martin Vetterli, Ali Zoubir, Marta Martinez-Camara

Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator tha ...

2015

A Hardware-in-the-Loop test platform for the performance assessment of a PMU-based Real-Time State Estimator for Active Distribution Networks

Mario Paolone, Paolo Romano, Marco Pignati, Lorenzo Zanni, Styliani Sarri

The paper describes the development of a Hardware- in-the-Loop (HIL) test platform for the performance assessment of a PMU-based sub-second linear Real-Time State Estimator (RTSE) for Active Distribution Networks (ADNs). The estimator relies on the availab ...

IEEE2015

Enhancing statistical performance of data-driven controller tuning via L2-regularization

Alireza Karimi

Noniterative data-driven techniques are design methods that allow optimal feedback control laws to be derived from input-output (I/O) data only, without the need of a model of the process. A drawback of these methods is that, in their standard formulation, ...

Pergamon-Elsevier Science Ltd2014

Ridge regression

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Sparsistency of $\ell_1$-Regularized $M$-Estimators

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Process Design and Optimization (MLS-S03): a Journey in Modeling, Optimization and Regression

Total Variation Regularization of Shape Signals

Towards Convenient Calibration for Cross-Ratio based Gaze Estimation

EMG-based learning approach for estimating wrist motion

Isotropic Inverse-Problem Approach for Two-Dimensional Phase Unwrapping

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

A Hardware-in-the-Loop test platform for the performance assessment of a PMU-based Real-Time State Estimator for Active Distribution Networks

Enhancing statistical performance of data-driven controller tuning via L2-regularization

Total Variation Regularization of Shape Signals

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost

Isotropic Inverse-Problem Approach for Two-Dimensional Phase Unwrapping

Process Design and Optimization (MLS-S03): a Journey in Modeling, Optimization and Regression

EMG-based learning approach for estimating wrist motion

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Towards Convenient Calibration for Cross-Ratio based Gaze Estimation

Enhancing statistical performance of data-driven controller tuning via L2-regularization

A Hardware-in-the-Loop test platform for the performance assessment of a PMU-based Real-Time State Estimator for Active Distribution Networks

Sparsistency of $\ell_1$-Regularized $M$-Estimators