• SHOGUN

  • Referenced in 103 articles [sw03517]
  • support vector machines, hidden Markov models, multiple kernel learning, linear discriminant analysis, and more. Most...
  • SimpleMKL

  • Referenced in 66 articles [sw12290]
  • SimpleMKL. Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor ... vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear ... from learning the combination, we solve a standard SVM optimization problem, where the kernel ... defined as a linear combination of multiple kernels. We propose an algorithm, named SimpleMKL...
  • SpicyMKL

  • Referenced in 9 articles [sw14765]
  • SpicyMKL: a fast algorithm for multiple kernel learning with thousands of kernels. We propose ... optimization algorithm for multiple kernel learning (MKL) called SpicyMKL, which is applicable to general convex...
  • EasyMKL

  • Referenced in 6 articles [sw32450]
  • EasyMKL: A scalable multiple kernel learning algorithm. The goal of Multiple Kernel Learning...
  • COFFIN

  • Referenced in 8 articles [sw04881]
  • fusion by concatenating feature spaces or multiple kernel learning. Unfortunately, they are not suited...
  • JKernelmachines

  • Referenced in 2 articles [sw10890]
  • based kernel combination methods such as Multiple Kernel Learning (MKL), and a recently published algorithm...
  • LIBXSMM

  • Referenced in 9 articles [sw23238]
  • deep learning primitives such as small convolutions targeting Intel Architecture. Small matrix multiplication kernels...
  • E-MaLeS

  • Referenced in 11 articles [sw15190]
  • prover E. E-MaLeS applies a kernel-based learning method to predict the run-time ... problem and dynamically constructs a schedule of multiple promising strategies that are tried in sequence...
  • PointCNN

  • Referenced in 7 articles [sw32557]
  • irregular and unordered, thus directly convolving kernels against features associated with the points, will result ... address these problems, we propose to learn an X-transformation from the input points ... generalization of typical CNNs to feature learning from point clouds, thus we call it PointCNN ... than state-of-the-art methods on multiple challenging benchmark datasets and tasks...
  • SMATER

  • Referenced in 1 article [sw30962]
  • architecture. Sparse matrix vector multiplication (SpMV) is an important computational kernel in traditional high-performance ... matrix during runtime. SMATER leverages a machine-learning model and retargetable back-end library...
  • Gazelle

  • Referenced in 1 article [sw38099]
  • growing popularity of cloud-based machine learning raises a natural question about the privacy guarantees ... such as SIMD (single instruction multiple data) addition, SIMD multiplication and ciphertext permutation. Second ... implement the Gazelle homomorphic linear algebra kernels which map neural network layers to optimized homomorphic...
  • ADOL-C

  • Referenced in 247 articles [sw00019]
  • ADOL-C: Automatic Differentiation of C/C++. We present...
  • ANSYS

  • Referenced in 685 articles [sw00044]
  • ANSYS offers a comprehensive software suite that spans...
  • ATLAS

  • Referenced in 198 articles [sw00056]
  • This paper describes the Automatically Tuned Linear Algebra...
  • CGAL

  • Referenced in 381 articles [sw00118]
  • The goal of the CGAL Open Source Project...
  • CLIFFORD

  • Referenced in 82 articles [sw00131]
  • CLIFFORD performs various computations in Grass mann and...
  • Coq

  • Referenced in 1856 articles [sw00161]
  • Coq is a formal proof management system. It...
  • CSDP

  • Referenced in 202 articles [sw00169]
  • CSDP, A C Library for Semidefinite Programming. This...
  • GAP

  • Referenced in 3068 articles [sw00320]
  • GAP is a system for computational discrete algebra...
  • GLOB

  • Referenced in 36 articles [sw00357]
  • GLOB -- a new VNS-based software for global...