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  • PDE-Net
  • Referenced in 63 articles [sw36963]
  • flexibility by learning both differential operators and the nonlinear responses. A special feature...

  • MatchNet
  • Referenced in 5 articles [sw31214]
  • MatchNet: Unifying feature and metric learning for patch-based ... matching. Motivated by recent successes on learning feature representations and on learning feature comparison functions...

  • IMOST
  • Referenced in 8 articles [sw02141]
  • provides integration-oriented, adaptation and dynamic learning features by considering all possibilities of a specific...

  • LVQ_PAK
  • Referenced in 30 articles [sw12122]
  • effective application of learning vector quantization algorithms, is presented. Two new features are included: fast ... into the class zones and the optimized-learning-rate algorithm OLVQ1...

  • Pse-in-One
  • Referenced in 41 articles [sw22407]
  • users themselves. These feature vectors can be easily combined with machine-learning algorithms to develop...

  • 3DMatch
  • Referenced in 6 articles [sw32561]
  • 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions. Matching local geometric features on real ... present 3DMatch, a data-driven model that learns a local volumetric patch descriptor for establishing ... model, we propose an unsupervised feature learning method that leverages the millions of correspondence labels...

  • Pegasos
  • Referenced in 103 articles [sw08752]
  • bound on the number of non-zero features in each example. Since the run-time ... resulting algorithm is especially suited for learning from large datasets. Our approach also extends...

  • PersistenceImages
  • Referenced in 35 articles [sw41418]
  • provides a multiscale description of the homological features within a dataset. A useful representation ... spaces with additional structure valuable to machine learning tasks. We convert ... machine learning tools, such as linear sparse support vector machines, which identify features containing discriminating...

  • MALSAR
  • Referenced in 5 articles [sw14319]
  • Joint Feature Selection; Robust Multi-Task Feature Learning; Trace-Norm Regularized Multi-Task Learning; Alternating...

  • mlr
  • Referenced in 31 articles [sw12357]
  • clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping ... feature selection. Extension of basic learners with additional operations common in machine learning, also allowing...

  • ArcFace
  • Referenced in 5 articles [sw33958]
  • main challenges in feature learning using Deep Convolutional Neural Networks (DCNNs) for large-scale face ... loss penalises the distance between the deep features and their corresponding class centres...

  • mdp
  • Referenced in 11 articles [sw14129]
  • collection of supervised and unsupervised learning algorithms and other data processing units that ... Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several...

  • DeCAF
  • Referenced in 28 articles [sw17856]
  • source implementation of these deep convolutional activation features, along with all associated network parameters ... representations across a range of visual concept learning paradigms...

  • Learn++.MF
  • Referenced in 5 articles [sw37993]
  • subspace approach for the missing feature problem. We introduce Learn++.MF, an ensemble-of-classifiers ... missing feature problem in supervised classification. Unlike most established approaches, Learn++.MF does not replace ... random subset of the available features. Instances with missing values are classified by the majority ... include the missing features. We show that Learn++.MF can accommodate substantial amount of missing...

  • GraRep
  • Referenced in 22 articles [sw32342]
  • show that our learned global representations can be effectively used as features in tasks such...

  • shap
  • Referenced in 50 articles [sw30901]
  • explain the output of any machine learning model. SHAP connects game theory with local explanations ... only possible consistent and locally accurate additive feature attribution method based on expectations...

  • TPOT
  • Referenced in 11 articles [sw18808]
  • process of designing and optimizing machine learning pipelines. In this paper we present TPOT v0.3 ... that optimizes a series of feature preprocessors and machine learning models with the goal...

  • LibDAI
  • Referenced in 15 articles [sw06422]
  • maximum probability states. Parameter learning is also supported. A feature comparison with other open source...

  • SPLATNet
  • Referenced in 4 articles [sw36664]
  • structure enabling hierarchical and spatially-aware feature learning, as well as joint 2D-3D reasoning...

  • ACL2s
  • Referenced in 11 articles [sw07734]
  • designed systems. Unfortunately, ACL2 has a steep learning curve. Thus, novices tend have a very ... ACL2 sedan. ACL2s includes many features for streamlining the learning process that are not found...