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Publications associées (543)

Learning with tensors: a framework based on convex optimization and spectral regularization

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...

Springer2014

Unified Strategy to Monoterpene Indole Alkaloids: Total Syntheses of (±)-Goniomitine, (±)-1,2-Dehydroaspidospermidine, (±)-Aspidospermidine, (±)-Vincadifformine, and (±)-Kopsihainanine A

Qian Wang, Jieping Zhu, Zhengren Xu, Olivier Wagnières

Total syntheses of (±)-goniomitine, (±)-1,2-dehydroaspidospermidine, (±)-aspidospermidine, (±)-vincadifformine, and (±)-kopsihainanine A were achieved featuring two common key steps: (1) a palladium-catalyzed decarboxylative vinylation that provides quick ...

Amer Chemical Soc2014

Posterior-based Sparse Representation for Automatic Speech Recognition

Hervé Bourlard, Afsaneh Asaei, David Imseng, Sara Bahaadini Beigy Zarandi

Posterior features have been shown to yield very good performance in multiple contexts including speech recognition, spoken term detection, and template matching. These days, posterior features are usually estimated at the output of a neural network. More ...

2014

Assessing Social Value in Open Data Initiatives: A Framework

Gianluigi Viscusi

Open data initiatives are characterized, in several countries, by a great extension of the number of data sets made available for access by public administrations, constituencies, businesses and other actors, such as journalists, international institutions ...

2014

A Method for the Assessment of the Optimal Parameter of Discrete-Time Switch Model

Mario Paolone, Reza Razzaghi, Chrysanthi Foti

This paper proposes a novel method for the optimal parameter selection of the discrete-time switch model used in circuit solvers that adopt the fixed admittance matrix nodal method (FAMNM) approach. As known, FAMNM-based circuit solvers allow to reach effi ...

Elsevier2014

Stable Myoelectric Control of a Hand Prosthesis using Non-Linear Incremental Learning

Barbara Caputo

Stable myoelectric control of hand prostheses remains an open problem. The only successful human–machine interface is surface electromyography, typically allowing control of a few degrees of freedom. Machine learning techniques may have the potential to re ...

2014

Receptive Fields Selection for Binary Feature Description

Pascal Fua, Zhiye Wang, Tomasz Piotr Trzcinski, Bin Fan

Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning based methods for designing local descriptor become more and more popul ...

Institute of Electrical and Electronics Engineers2014

Learning Separable Filters with Shared Parts

Bugra Tekin

Learned image features can provide great accuracy in many Computer Vision tasks. However, when the convolution filters used to learn image features are numerous and not separable, feature extraction becomes computationally demanding and impractical to use ...

2013

Separable Filter Learning with Tensor Decomposition

Bugra Tekin

2013

Inverse Solutions for Brain Computer Interface

José del Rocio Millán Ruiz, Mohit Kumar Goel

Inverse solution allows to estimate sources that generate a given scalp EEG topography. Recently, it has been used in Brain Computer Interfaces (BCIs) to extract robust features based on the hypothesis that projection onto the source space (high dimensiona ...

EPFL2013

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