• LowRankModels

  • Referenced in 37 articles [sw27002]
  • easy to mix and match loss functions and regularizers to construct a model suitable ... particular, it supports: using different loss functions for different columns of the data array, which...
  • isotone

  • Referenced in 34 articles [sw20811]
  • simple chain constraints. Besides of general convex functions we extend existing PAVA implementations in terms ... This methodology is applied on specific loss functions relevant in statistics. Both approaches are implemented...
  • N-way Toolbox

  • Referenced in 30 articles [sw12996]
  • models with a weighted least squares loss function (including MILES); Predicting scores for new samples...
  • FPINNs

  • Referenced in 27 articles [sw40570]
  • constructing the residual in the loss function using both automatic differentiation for the integer-order...
  • AdaBoost-SAMME

  • Referenced in 26 articles [sw19134]
  • class of Fisher-consistent loss functions for multi-class classification. As shown in this paper...
  • bmrm

  • Referenced in 23 articles [sw11016]
  • package comes with lot of loss functions for machine learning which make it powerful...
  • Ginsim

  • Referenced in 29 articles [sw09090]
  • types of experimental perturbations, such as loss-of-function mutations or ectopically induced gene expression...
  • pertsaus2

  • Referenced in 17 articles [sw15442]
  • details are given for least squares loss functions and for least absolute deviations. The weighted...
  • ENDER

  • Referenced in 15 articles [sw12831]
  • ensemble. We consider different loss functions and minimization techniques often encountered in the boosting framework...
  • DiSCO

  • Referenced in 12 articles [sw28439]
  • efficiency for minimizing self-concordant empirical loss functions, and discuss the results for distributed ridge ... binary classification with a smoothed hinge loss. In a standard setting for supervised learning, where...
  • Vowpal Wabbit

  • Referenced in 11 articles [sw28398]
  • sparse gradient descent (GD) on a loss function (several are available), The code should...
  • PANTHER

  • Referenced in 15 articles [sw22973]
  • used to define HMMs, but gene ontology functional annotations can now be made ... designed to represent gain and loss of function by ancestral genes during evolution. Finally, PANTHER...
  • geomstats

  • Referenced in 9 articles [sw24373]
  • intuitive choices of Machine Learning loss functions. We also give the corresponding Riemannian gradients...
  • SpicyMKL

  • Referenced in 9 articles [sw14765]
  • which is applicable to general convex loss functions and general types of regularization. The proposed...
  • CosFace

  • Referenced in 5 articles [sw39109]
  • address this problem, recently several loss functions such as center loss, large margin softmax loss ... this paper, we propose a novel loss function, namely large margin cosine loss (LMCL...
  • ArcFace

  • Referenced in 5 articles [sw33958]
  • recognition is the design of appropriate loss functions that enhance discriminative power. Centre loss penalises ... incorporate margins in well-established loss functions in order to maximise face class separability ... paper, we propose an Additive Angular Margin Loss (ArcFace) to obtain highly discriminative features...
  • GANSim

  • Referenced in 4 articles [sw40967]
  • patterns using the original GAN’s loss function, then appropriate latent vectors are searched ... introducing an extra condition-based loss function and adjusting the architecture of the generator ... growing of GANs. The condition-based loss function is defined as the inconsistency between...
  • DSCOVR

  • Referenced in 6 articles [sw28397]
  • large linear models with convex loss functions, and propose a family of randomized primal-dual...
  • RBoost

  • Referenced in 3 articles [sw29975]
  • Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners. AdaBoost ... AdaBoost stems from the exponential loss function, which puts unrestricted penalties to the misclassified samples ... RBoost1 and RBoost2 optimize a nonconvex loss function of the classification margin. Because the penalties ... previous base learners. Besides the loss function, at each boosting iteration, RBoost1 and RBoost2...
  • actuar

  • Referenced in 22 articles [sw06079]
  • functions , Additional actuarial science functionality, mostly in the fields of loss distributions, risk theory (including...