Concept

Feature selection

Related publications (543)

FEATURE AND SCORE LEVEL COMBINATION OF SUBSPACE GAUSSIANS IN LVCSR TASK

In this paper, we investigate employment of discriminatively trained acoustic features modeled by Subspace Gaussian Mixture Models (SGMMs) for Rich Transcription meeting recognition. More specifically, first, we focus on exploiting various types of complex ...

Idiap2013

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Volkan Cevher, Anastasios Kyrillidis

The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the

\ell_2

-data error objective and the

\ell_1

-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection ...

IEEE2012

Selection and Aggregation of Ranking Criteria for Retrieval from Scientific Publication Databases

Martin Veselý

Selection and aggregation of ranking criteria became an important topic in information retrieval as search is getting more specialized and as volume of electronically available information grows. In this context, document ranking has undergone a shift from ...

EPFL2012

Unsupervised change detection with kernels

Devis Tuia

In this letter, an unsupervised kernel-based approach to change detection is introduced. Nonlinear clustering is utilized to partition in two a selected subset of pixels representing both changed and unchanged areas. Once the optimal clustering is obtained ...

Ieee-Inst Electrical Electronics Engineers Inc2012

Experimental Validation of a Hybrid Computational Model for Selective Stimulation Using Transverse Intrafascicular Multichannel Electrodes

Silvestro Micera, Marco Capogrosso, Stanisa Raspopovic

Recently a hybrid model based on the finite element method and on a compartmental biophysical representation of peripheral nerve fibers and intraneural electrodes was developed founded on experimental physiological and histological data. The model appeared ...

2012

A Multi-Lead ECG Classification Based on Random Projection Features

David Atienza Alonso, Iva Bogdanova Vandergheynst

This paper presents a novel method for classification of multilead electrocardiogram (ECG) signals. The feature extraction is based on the random projection (RP) concept for dimensionality reduction. Furthermore, the classification is performed by a neuro- ...

IEEE Press2012

Enhanced change detection using nonlinear feature extraction

Devis Tuia, Giona Matasci

This paper presents an application of the kernel principal component analysis aiming at aligning optical images before the application of change detection techniques. The approach relies on the extraction of nonlinear features from a selected subset of pix ...

2012

On the Challenge of Classifying 52 Hand Movements from Surface Electromyography

Barbara Caputo, Ilja Kuzborskij

The level of dexterity of myoelectric hand prostheses depends to large extent on the feature representation and subsequent classification of surface electromyography signals. This work presents a comparison of various feature extraction and classification ...

2012

A Multi-Lead Ecg Classification Based On Random Projection Features

David Atienza Alonso, Francisco Javier Rincon Vallejos, Iva Bogdanova Vandergheynst

This paper presents a novel method for classification of multi-lead electrocardiogram (ECG) signals. The feature extraction is based on the random projection (RP) concept for dimensionality reduction. Furthermore, the classification is performed by a neuro ...

IEEE Press2012

Learning Near-optimal Decision Rules for Energy Efficient Building Control

Colin Neil Jones

Recent studies suggest that advanced optimization based control methods such as model predictive control (MPC) can increase energy efficiency of buildings. However, adoption of these methods by industry is still slow, as building operators are used to work ...

2012

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Volkan Cevher, Anastasios Kyrillidis

The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the

\ell_2

-data error objective and the

\ell_1

-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection ...

IEEE2012