Results 121 to 130 of about 210,501 (299)

Basic metric learning

, 2008
This report presents a a novel Multiple Kernel Learning (MKL) algorithm for the 1-class support vector machine. The emphasis is placed on viewing the CBIR task with relevance feedback as a metric learning problem, where each image has 11 different ...
Hussain, Zakria, Shawe-Taylor, John, Saunders, Craig, Pasupa, Kitsuchart   +3 more
core  

Similarity Metric Learning

, 2021
International audienceSimilarity metric learning models the general semantic similarities and distances between objects and classes of objects (e.g. persons) in order to recognise them.
Baskurt, Atilla, Duffner, Stefan, Garcia, Christophe, Idrissi, Khalid   +3 more
core   +2 more sources

Metric Learning for Phoneme Perception

CoRR, 2018
Metric functions for phoneme perception capture the similarity structure among phonemes in a given language and therefore play a central role in phonology and psycho-linguistics. Various phenomena depend on phoneme similarity, such as spoken word recognition or serial recall from verbal working memory. This study presents a new framework for learning a
Yair Lakretz, Gal Chechik, Evan-Gary Cohen, Alessandro Treves, Naama Friedmann   +4 more
openaire   +2 more sources

Efficacy of Intermittent Theta‐Burst Stimulation for Prolonged Disorders of Consciousness: A Prospective, Randomized, Controlled Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu, Jun Hu, Qianqian Wu, Min Wu, Yamei Yu, Hangcheng Li, Jian Gao, Jingqi Li, Nai Ding, Jie Yu, Benyan Luo   +10 more
wiley   +1 more source

Making metric learning algorithms invariant to transformations using a projection metric on Grassmann manifolds

, 2019
The requirement for suitable ways to measure the distance or similarity between data is omnipresent in machine learning, pattern recognition and data mining, but extracting such good metrics for particular problems is in general challenging. This has led
Ehsani, Mohammad Saeid, Grigat, Rolf-Rainer, Goudarzi, Zahra, Adibi, Peyman   +3 more
core  

Kernel Density Metric Learning

, 2013
This paper introduces a supervised metric learning algorithm, called kernel density metric learning (KDML), which is easy to use and provides nonlinear, probability-based distance measures.
Chen, Wenlin, He, Yujie, Chen, Yixin
core   +1 more source

Paramagnetic Rim Lesions Are Associated With Trans‐Synaptic Degeneration of the Visual Pathway in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Retrograde trans‐synaptic degeneration (rTSD) from posterior visual pathway lesions in multiple sclerosis (MS) is characterized by hemi‐macular ganglion cell‐inner plexiform layer (GCIPL) thinning and contralateral visual field loss.
Abdul Jaber Tayem, Angel Liu, Sargis Manukyan, Mustafa Subhi, Elaina Luskin, Bryan Quah, Sreekanth Madhusoodhanan Nair, Arzu C. Has Silemek, Gabriela Zabala, Yujie Cui, Laura Locke, Paula Barreras, Marwa Kaisey, Vinicius Calsavara, Daniel S. Reich, Nancy L. Sicotte, Pascal Sati, Omar Al‐Louzi   +17 more
wiley   +1 more source

Metric-Based Model Selection For Time-Series Forecasting [PDF]

Metric-based methods, which use unlabeled data to detect gross differences in behavior away from the training points, have recently been introduced for model selection, often yielding very significant improvements over alternatives (including cross ...
Yoshua Bengio, Nicolas Chapados
core  

Tree edit distance learning via adaptive symbol embeddings [PDF]

, 2018
Metric learning has the aim to improve classification accuracy by learning a distance measure which brings data points from the same class closer together and pushes data points from different classes further apart.
Paaßen, Benjamin, Micheli, Alessio, Gallicchio, Claudio, Hammer, Barbara   +3 more
core  

Discriminative Semantic Subspace Analysis for Relevance Feedback

, 2016
Content-based image retrieval (CBIR) has attracted much attention during the past decades for its potential practical applications to image database management. A variety of relevance feedback (RF) schemes have been designed to bridge the gap between low-
Zhang, Lining, Lining Zhang, Shao, Ling, Shum, Hubert P. H., Ling Shao, Hubert P. H. Shum, Shum, Hubert   +6 more
core   +1 more source