Results 31 to 40 of about 1,273,358 (272)
, 2015 Sparse representation models a signal as a linear combination of a small number of dictionary atoms. As a generative model, it requires the dictionary to be highly redundant in order to ensure both a stable high sparsity level and a low reconstruction ...
Nasrabadi, Nasser M. +2 more
core +1 more source
Lexikos, 2013 Idioms, sayings and proverbs (referred to here as 'phrasemes'), are a central part of the English language. However, it is often difficult for learners of English as an Additional Language (EAL) to choose the correct headword when looking for such ...
Julia Miller
doaj +1 more source
Uluslararası Türk Lehçe Araştırmaları Dergisi, 2021 Idioms and proverbs, which can be witnessed since the first periods of Turkic, not only reflect the change and intensity of meaning in the language, but also provide in information about the age of the language.
Nurdan BESLİ
doaj +1 more source
Learning computationally efficient dictionaries and their implementation as fast transforms [PDF]
, 2015 Dictionary learning is a branch of signal processing and machine learning that aims at finding a frame (called dictionary) in which some training data admits a sparse representation. The sparser the representation, the better the dictionary.
Gribonval, Rémi, Magoarou, Luc Le
core +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization [PDF]
, 2014 We consider the problem of sparse coding, where each sample consists of a sparse linear combination of a set of dictionary atoms, and the task is to learn both the dictionary elements and the mixing coefficients.
Agarwal, Alekh +3 more
core
Statistical Mechanics of Dictionary Learning
, 2013 Finding a basis matrix (dictionary) by which objective signals are represented sparsely is of major relevance in various scientific and technological fields. We consider a problem to learn a dictionary from a set of training signals. We employ techniques
Ayaka Sakata +11 more
core +1 more source
Arthritis Care &Research, EarlyView.Objective This study aimed to characterize the pharmacokinetics, pharmacodynamics, safety, and exploratory efficacy of subcutaneous belimumab in pediatric patients with active systemic lupus erythematosus (SLE) receiving standard therapy. Methods This single‐arm, multicenter, open‐label trial (GSK study 200908; ClinicalTrials.gov identifier ...
Hermine I. Brunner +14 more
wiley +1 more source
Automatic Addition of Genre Information in a Japanese Dictionary
Acta Linguistica Asiatica, 2012 This article presents the method used for the automatic addition of genre information to the Japanese entries in a Japanese-French dictionary. The dictionary is intended for a wide audience, ranging from learners of Japanese as a second language to ...
Raoul BLIN
doaj +1 more source
Dictionary-based Tensor Canonical Polyadic Decomposition
, 2017 To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary.
Cohen, Jérémy E., Gillis, Nicolas
core +1 more source