• SimpleMKL

  • Referenced in 62 articles [sw12290]
  • vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear ... address the MKL problem through a weighted 2-norm regularization formulation with ... additional constraint on the weights that encourages sparse kernel combinations. Apart from learning the combination...
  • CGAL

  • Referenced in 362 articles [sw00118]
  • points, 2D additively weighted Voronoi diagrams, and segment Voronoi diagrams), polygons (Boolean operations, offsets, straight ... objects and predicates are regrouped in CGAL Kernels. Finally, the Support Library offers geometric object...
  • NESToolbox

  • Referenced in 4 articles [sw19592]
  • series, which are based on Gaussian-kernel weight functions. Cross-correlation estimation ... makes alternative approaches such as the Gaussian-kernel-based cross correlation [1], the nonlinear Gaussian ... kernel-based mutual information [2] or the Event Synchronization function [3] available under a single ... well as nonlinear trends, power spectra and weighted scatterplots. The usage of these functions...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • classical pattern recognition algorithms such as kernel Fisher discriminant analysis and extensions to unsupervised learning ... control are available. Robustness, sparseness and weightings can be incorporated into LS-SVMs where needed ... primal-dual formulations have been given to kernel PCA, kernel CCA and kernel PLS. Recent...
  • KeBABS

  • Referenced in 1 article [sw15427]
  • kernel formulation, other kernels like the weighted degree kernel or the shifted weighted degree kernel ... weighting of positions are included as special cases. An annotation-specific variant of the kernels ... dense or sparse format for all available kernels which can be used with methods implemented ... results, the package computes feature weights for all SVMs and prediction profiles which show...
  • KBAL

  • Referenced in 3 articles [sw36072]
  • implementation of kernel balancing. Investigators often use matching and weighting techniques to adjust for differences ... treated and control groups. This paper introduces kernel balancing, a method designed to reduce this ... searches or balance tests. The weights derived by kernel balancing (1) achieve approximate mean balance...
  • SyncSpecCnn

  • Referenced in 5 articles [sw26163]
  • spectral CNN method that enables weight sharing by parameterizing kernels in the spectral domain spanned...
  • QTM

  • Referenced in 3 articles [sw14198]
  • constructed from atomic data using weighted Gaussian isotropic kernel functions and a two-level clustering...
  • ECOC

  • Referenced in 5 articles [sw14443]
  • density, attenuated, loss-based, probabilistic kernel-based, and loss-weighted) with the parameters defined...
  • parallelMCMCcombine

  • Referenced in 3 articles [sw21115]
  • averaging across subset samples, weighted averaging across subsets samples, and kernel smoothing across subset samples...
  • scgwr

  • Referenced in 1 article [sw28372]
  • algorithm for large-scale geographically weighted regression with polynomial kernels. While a number of studies...
  • DoReFa-Net

  • Referenced in 4 articles [sw36246]
  • bitwidth weights and activations/gradients respectively, DoReFa-Net can use bit convolution kernels to accelerate both ... derived from AlexNet that has 1-bit weights, 2-bit activations, can be trained from...
  • BinaryNet

  • Referenced in 11 articles [sw35872]
  • time. At training-time the binary weights and activations are used for computing the parameters ... wrote a binary matrix multiplication GPU kernel with which it is possible...
  • TMG

  • Referenced in 10 articles [sw04180]
  • collections involve techniques from linear algebra. These kernels typically operate on data that are presented ... effect of stemming and different term-weighting policies on the performance of querying and clustering...
  • MOLT

  • Referenced in 4 articles [sw34473]
  • proposed method relies on a special kernel based formulation of the solutions found ... such a framework, a high order weighted essentially non-oscillatory methodology and a nonlinear filter ... Kutta method. Moreover, theoretical investigations of the kernel based formulation combined with an explicit...
  • Pyclaw

  • Referenced in 15 articles [sw06504]
  • code while employing automatically wrapped Fortran kernels for computationally intensive routines, and using Python bindings ... PyWENO for generation of efficient high-order weighted essentially nonoscillatory reconstruction code. The simplicity, capability...
  • kalepy

  • Referenced in 1 article [sw37028]
  • estimation and sampling. The kalepy package performs kernel density estimation on multidimensional data ... provides optional weightings, reflecting boundary conditions, an arbitrary number of dimensions, numerous kernel functions, built...
  • CoMIK

  • Referenced in 1 article [sw35270]
  • site as reference. Existing position-aware string kernels have been shown to be useful ... interpret the weight vector for the complex setting of multiple multi-instance kernels...
  • PointCNN

  • Referenced in 6 articles [sw32557]
  • irregular and unordered, thus directly convolving kernels against features associated with the points, will result ... promote two causes. The first is the weighting of the input features associated with...
  • gwfa

  • Referenced in 0 articles [sw17779]
  • points. The Geographically Weighted approach consists in applying a kernel that describes...