Concept

Dictionary

Related publications (112)

Bilinear Generalized Approximate Message Passing—Part II: Applications

In this paper, we extend the generalized approximate message passing (G-AMP) approach, originally proposed for high-dimensional generalized-linear regression in the context of compressive sensing, to the generalized-bilinear case. In Part I of this two-par ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Dictionary learning over large distributed models via dual-ADMM strategies

Ali H. Sayed

We consider the problem of dictionary learning over large scale models, where the model parameters are distributed over a multi-agent network. We demonstrate that the dual optimization problem for inference is better conditioned than the primal problem and ...

IEEE2014

Parametric dictionary learning for graph signals

Pascal Frossard, David Shuman

We propose a parametric dictionary learning algorithm to design structured dictionaries that sparsely represent graph signals. We incorporate the graph structure by forcing the learned dictionaries to be concatenations of subdictionaries that are polynomia ...

2013

LAYOUT ASSESSMENT METHOD AND SYSTEM

Frank Grégoire Jean de Morsier, Virginia Estellers Casas, Nathalie Casati, Maria Gabrani

Candidate layout patterns can be assessed using a sparse pattern dictionary of known design layout patterns by determining sparse coefficients for each candidate pattern, reconstructing the respective candidate pattern, and determining reconstruction error ...

U.S. Patent and Trademark Office; U.S. DEPARTMENT OF COMMERCE2013

A convex optimization framework for global tractography

Jean-Philippe Thiran, Alessandro Daducci, Alia Lemkaddem

In this article we present a novel approach for diffusion MRI global tractography. Our formulation models the signal in each voxel as a linear combination of fiber-tract basis func- tions, which consist of a comprehensive set of plausible fiber tracts that ...

2013

Convexity in source separation: Models, geometry, and algorithms

Volkan Cevher, Afsaneh Asaei, Quoc Tran Dinh, Luca Baldassarre

Source separation, or demixing, is the process of extracting multiple components entangled within a signal. Contemporary signal processing presents a host of difficult source separation problems, from interference cancellation to background subtraction, bl ...

2013

Probabilistic Lexical Modeling and Unsupervised Training for Zero-Resourced ASR

Ramya Rasipuram, Marzieh Razavi

Standard automatic speech recognition (ASR) systems rely on transcribed speech, language models, and pronunciation dictionaries to achieve state-of-the-art performance. The unavailability of these resources constrains the ASR technology to be available for ...

2013

Error Correction Mechanism for Five-Key Chording Keyboards

Pierre Dillenbourg, Bixio Rimoldi, Adrian Dan Tarniceriu

As different text input devices lead to different typing error patterns, considering the device characteristics when designing an error correction mechanism can lead to significantly improved results. In this paper, we propose and evaluate a spelling algor ...

IEEE2013

Probabilistic Lexical Modeling and Grapheme-based Automatic Speech Recognition

Ramya Rasipuram

Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems use phonemes as subword units. Thus, development of ASR system for a new language or domain depends upon the availability of a phoneme lexicon in the target language. In th ...

Idiap2013

Robust joint reconstruction of misaligned images using semi-parametric dictionaries

Pierre Vandergheynst, Gilles Puy

We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Theoretical results about the co ...

2012

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