Concept

Ridge regression

Related publications (288)

Regularized Bundle Methods for Convex and Non-Convex Risks

Machine learning is most often cast as an optimization problem. Ideally, one expects a convex objective function to rely on efficient convex optimizers with nice guarantees such as no local optima. Yet, non-convexity is very frequent in practice and it may ...

2012

A Real-Time Deformable Detector

Pascal Fua, François Fleuret, Karim Ali, David Hasler

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform base ...

Institute of Electrical and Electronics Engineers2012

Structural monitoring: identification and location of an impact on a structurally dissipating rock-shed structure using the inverse method

Fabrice Dupray

In this study we developed an experimental method to identify the impact force on a reinforced concrete slab. A transfer function obtained experimentally between the acceleration response and the force history applied to a point of the structure was used. ...

2012

Unified Framework Of Feature Based Adaptation For Statistical Speech Synthesis And Recognition

Lakshmi Babu Saheer

The advent of statistical parametric speech synthesis has paved new ways to a unified framework for hidden Markov model (HMM) based text to speech synthesis (TTS) and automatic speech recognition (ASR). The techniques and advancements made in the field of ...

Ecole Polytechnique Federale de Lausanne (EPFL)2012

Bayesian Denoising Of Generalized Poisson Processes With Finite Rate Of Innovation

Michaël Unser, Arash Amini, Ulugbek Kamilov

We investigate the problem of the optimal reconstruction of a generalized Poisson process from its noisy samples. The process is known to have a finite rate of innovation since it is generated by a random stream of Diracs with a finite average number of im ...

Ieee2012

Bayesian Denoising of Generalized Poisson Processes with Finite Rate of Innovation

Michaël Unser, Azin Amini, Ulugbek Kamilov

IEEE2012

Reconstruction Of Biomedical Images And Sparse Stochastic Modeling

Michaël Unser, Emrah Bostan, Ulugbek Kamilov

We propose a novel statistical formulation of the image-reconstruction problem from noisy linear measurements. We derive an extended family of MAP estimators based on the theory of continuous-domain sparse stochastic processes. We highlight the crucial rol ...

Ieee2012

Reconstruction of Biomedical Images and Sparse Stochastic Modeling

Michaël Unser, Emrah Bostan, Ulugbek Kamilov

IEEE2012

Fast Geodesic Active Fields for Image Registration based on Splitting and Augmented Lagrangian Approaches

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso

In this paper we present an efficient numerical scheme for the recently introduced Geodesic Active Fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, data-te ...

2011

Chebyshev polynomial approximation for transductive learning on graphs

Nathanaël Perraudin

The goal of transductive learning is to find a way to recover the labels of lots of data with only a few known samples. In this work, we will work on graphs for two reasons. First, it’s possible to construct a graph from a given dataset with features. The ...

2011

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