Publications associées à Régression polynomiale

An algebraic least squares reduced basis method for the solution of nonaffinely parametrized Stokes equations

Alfio Quarteroni, Simone Deparis, Andrea Manzoni, Niccolò Dal Santo

In this paper we propose a new, purely algebraic, Petrov-Galerkin reduced basis (RB) method to solve the parametrized Stokes equations, where parameters serve to identify the (variable) domain geometry. Our method is obtained as an algebraic least squares ...

ELSEVIER SCIENCE SA2019

Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios

Andreas Peter Burg, Andreas Toftegaard Kristensen

In-band full-duplex systems allow for more efficient use of temporal and spectral resources by transmitting and receiving information at the same time and on the same frequency. However, this creates a strong self-interference signal at the receiver, makin ...

IEEE2019

A data-driven model for the air-cooling condenser of large-scale coal-fired power plants based on data reconciliation and support vector regression

François Maréchal, Ivan Daniel Kantor, Ligang Wang, Xiang Li, Jean-Loup Sylvain Robineau

The performance of a direct air-cooling condenser under operation is rather complicated, as it is interactively affected by the operating conditions (e.g., the mode of air fans) and ambient conditions (e.g., temperature and wind speed). To understand the c ...

2018

Sensorless Position Detection Framework for a Multi-state Switched Reluctance Actuator of a Textile Machine

Yves Perriard, Yoan René Cyrille Civet, Paolo Germano, Xinchang Liu

Sensorless needle position detection for the actuator of a textile machine is challenging because of its multi current levels used and the transient state when the current changes. A local regression method can be used to represent the variation of inducta ...

IEEE2018

Implementing Fusion Techniques for the Classification of Paralinguistic Information

Jilt Sebastian

This work tests several classification techniques and acoustic features and further combines them using late fusion to classify paralinguistic information for the ComParE 2018 challenge. We use Multiple Linear Regression (MLR) with Ordinary Least Squares ( ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Methodology And Convergence Rates For Functional Time Series Regression

Victor Panaretos, Tung Huy Pham

The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite-dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose inverse is by defi ...

STATISTICA SINICA2018

MATHICSE Technical Report : An algebraic least squares reduced basis method for the solution of parametrized Stokes equations

Alfio Quarteroni, Simone Deparis, Andrea Manzoni, Niccolò Dal Santo

MATHICSE2018

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Golnooshsadat Elhami, Michalina Wanda Pacholska

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is of ...

2018

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Régression polynomiale

Automatic L2 Regularization for Multiple Generalized Additive Models

An algebraic least squares reduced basis method for the solution of nonaffinely parametrized Stokes equations

Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios

A data-driven model for the air-cooling condenser of large-scale coal-fired power plants based on data reconciliation and support vector regression

Sensorless Position Detection Framework for a Multi-state Switched Reluctance Actuator of a Textile Machine

Implementing Fusion Techniques for the Classification of Paralinguistic Information

Methodology And Convergence Rates For Functional Time Series Regression

From ice phase to liquid precipitation at the ground level: weather radar and machine learning

MATHICSE Technical Report : An algebraic least squares reduced basis method for the solution of parametrized Stokes equations

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Graph Chatbot

Chattez avec Graph Search

Automatic L2 Regularization for Multiple Generalized Additive Models

Sampling at unknown locations: Uniqueness and reconstruction under constraints

An algebraic least squares reduced basis method for the solution of nonaffinely parametrized Stokes equations

Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios

A data-driven model for the air-cooling condenser of large-scale coal-fired power plants based on data reconciliation and support vector regression

Sensorless Position Detection Framework for a Multi-state Switched Reluctance Actuator of a Textile Machine

Implementing Fusion Techniques for the Classification of Paralinguistic Information

From ice phase to liquid precipitation at the ground level: weather radar and machine learning

Methodology And Convergence Rates For Functional Time Series Regression

MATHICSE Technical Report : An algebraic least squares reduced basis method for the solution of parametrized Stokes equations