• Manopt

  • Referenced in 117 articles [sw08493]
  • Such structured constraints appear pervasively in machine learning applications, including low-rank 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 k-nearest 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 auto-annotation. Image auto-annotation ... distance. TagProp allows the integration of metric learning by directly maximizing the log-likelihood ... 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...
  • metric-learn

  • Referenced in 3 articles [sw35420]
  • metric-learn: metric learning algorithms in Python. metric-learn is an open source Python package ... implementing supervised and weakly-supervised distance metric learning algorithms. As part of scikit-learn-contrib ... pipelining with other machine learning estimators. metric-learn is thoroughly tested and available on PyPi...
  • pyDML

  • Referenced in 3 articles [sw35421]
  • pyDML: A Python Library for Distance Metric Learning. pyDML is an open-source 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 state-of-the-art 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 patch-based 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 Learning-Based 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 few-shot learning. Few-shot learning has become ... task sample set, resulting in learning a task-dependent metric space. Moreover, we propose ... auxiliary task co-training to learn a task-dependent metric space. The resulting few-shot ... learning model based on the task-dependent scaled metric achieves state...
  • FLAME

  • Referenced in 3 articles [sw36879]
  • Large-scale 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...