
Manopt
 Referenced in 117 articles
[sw08493]
 Such structured constraints appear pervasively in machine learning applications, including lowrank matrix completion, sensor ... camera network registration, independent component analysis, metric learning, dimensionality reduction and so on. The Manopt...

LMNN
 Referenced in 81 articles
[sw29754]
 Large Margin Nearest Neighbor (LMNN), a metric learning algorithm first introduced by Kilian Q. Weinberger ... Saul in 2005. LMNN is a metric learning algorithm to improve knearest neighbor classification ... learning a generalized Euclidean metric Equation especially for nearest neighbor classification...

TagProp
 Referenced in 17 articles
[sw11682]
 TagProp: Discriminative metric learning in nearest neighbor models for image autoannotation. Image autoannotation ... distance. TagProp allows the integration of metric learning by directly maximizing the loglikelihood ... optimally combine a collection of image similarity metrics that cover different aspects of image content...

GSML
 Referenced in 4 articles
[sw35600]
 GSML: A Unified Framework for Sparse Metric Learning. There has been significant recent interest ... sparse metric learning (SML) in which we simultaneously learn both a good distance metric ... Unfortunately, the performance of existing sparse metric learning approaches is usually limited because the authors ... paper, we propose a Generalized Sparse Metric Learning method (GSML). This novel framework offers...

metriclearn
 Referenced in 3 articles
[sw35420]
 metriclearn: metric learning algorithms in Python. metriclearn is an open source Python package ... implementing supervised and weaklysupervised distance metric learning algorithms. As part of scikitlearncontrib ... pipelining with other machine learning estimators. metriclearn is thoroughly tested and available on PyPi...

pyDML
 Referenced in 3 articles
[sw35421]
 pyDML: A Python Library for Distance Metric Learning. pyDML is an opensource python library ... provides a wide range of distance metric learning algorithms. Distance metric learning can be useful...

dml
 Referenced in 3 articles
[sw20804]
 package dml: Distance Metric Learning in R. The stateoftheart algorithms for distance ... metric learning, including global and local methods such as Relevant Component Analysis, Discriminative Component Analysis ... Fisher Discriminant Analysis, etc. These distance metric learning methods are widely applied in feature extraction...

MatchNet
 Referenced in 5 articles
[sw31214]
 MatchNet: Unifying feature and metric learning for patchbased matching. Motivated by recent successes...

Isomap
 Referenced in 11 articles
[sw31686]
 that uses easily measured local metric information to learn the underlying global geometry...

RALF
 Referenced in 4 articles
[sw33955]
 exploration and exploitation sampling criteria that is learned online during the sampling process ... find more representative labels for metric learning in comparison to the other one. Additionally...

ADASYN
 Referenced in 18 articles
[sw36457]
 machine learning data sets show the effectiveness of this method across five evaluation metrics...

GANomaly
 Referenced in 5 articles
[sw41240]
 result, a larger distance metric from this learned data distribution at inference time is indicative...

Metrics
 Referenced in 1 article
[sw09996]
 Metrics: Evaluation metrics for machine learning: Metrics is a set of evaluation metrics that...

MLmetrics
 Referenced in 3 articles
[sw26428]
 package MLmetrics: Machine Learning Evaluation Metrics. A collection of evaluation metrics, including loss, score...

BLEURT
 Referenced in 1 article
[sw39469]
 BLEURT: a Transfer LearningBased Metric for Natural Language Generation. BLEURT is an evaluation metric ... BLEU and BERTscore. BLEURT is a trained metric, that is, it is a regression model ... found in our ACL paper BLEURT: Learning Robust Metrics for Text Generation and our blog...

drtoolbox
 Referenced in 1 article
[sw39922]
 techniques for dimensionality reduction and metric learning. A large number of implementations was developed from...

CPLFW
 Referenced in 1 article
[sw39584]
 data driven machine learning methods, the performance on the database approaches nearly 100%. However ... attributes classification. We evaluate several metric learning and deep learning methods on the new database...

TADAM
 Referenced in 1 article
[sw41279]
 TADAM: Task dependent adaptive metric for improved fewshot learning. Fewshot learning has become ... task sample set, resulting in learning a taskdependent metric space. Moreover, we propose ... auxiliary task cotraining to learn a taskdependent metric space. The resulting fewshot ... learning model based on the taskdependent scaled metric achieves state...

FLAME
 Referenced in 3 articles
[sw36879]
 Largescale Almost Matching Exactly), learns a distance metric for matching using a hold...

MOE
 Referenced in 3 articles
[sw36871]
 metric optimization engine; a new open source, machine learning service for optimal experiment design...