• SVMlight

  • Referenced in 264 articles [sw04076]
  • regression, and for the problem of learning a ranking function. The optimization algorithms used ... includes two efficient estimation methods for both error rate and precision/recall. XiAlpha-estimates [Joachims, 2002a ... this version is an algorithm for learning ranking functions [Joachims, 2002c]. The goal...
  • FrodoKEM

  • Referenced in 17 articles [sw35260]
  • cautious parameterizations of the well-studied learning with errors problem, which in turn has close...
  • HyFIS

  • Referenced in 13 articles [sw24184]
  • tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation ... data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system...
  • RCV1

  • Referenced in 122 articles [sw07279]
  • taxonomies, and the corrections necessary to remove errorful data. We refer to the original data ... benchmark several widely used supervised learning methods on RCV1-v2, illustrating the collection’s properties...
  • Evolino

  • Referenced in 19 articles [sw36450]
  • search for sequence learning. Current Neural Network learning algorithms are limited in their ability ... RNNs) suffer from a vanishing error signal that prevents learning from inputs...
  • SIMBICON

  • Referenced in 7 articles [sw21525]
  • changes in direction and speed. Feedback-error learning is applied to learn predictive torque models...
  • CNTK

  • Referenced in 9 articles [sw21056]
  • Toolkit (https://cntk.ai), is a unified deep-learning toolkit that describes neural networks ... implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple...
  • SHIELD

  • Referenced in 7 articles [sw20121]
  • work, we describe an optimized Ring Learning With Errors (RLWE) based implementation of a variant...
  • TheCommitteeMachine

  • Referenced in 5 articles [sw38983]
  • transitions and compute the optimal learning and generalization errors in the teacher-student scenario ... committee machine that allows optimal learning in polynomial time for a large set of parameters ... regimes in which a low generalization error is information-theoretically achievable while the AMP algorithm...
  • SuLQ

  • Referenced in 128 articles [sw11355]
  • noise -- much less than the sampling error -- provided the total number of queries is sublinear ... operate in the in the statistical query learning model...
  • VAMPnets

  • Referenced in 19 articles [sw32927]
  • VAMPnets: Deep learning of molecular kinetics. There is an increasing demand for computing the relevant ... step will lead to large modeling errors. Here we employ the variational approach for Markov ... processes (VAMP) to develop a deep learning framework for molecular kinetics using neural networks, dubbed...
  • Quake

  • Referenced in 5 articles [sw12012]
  • read quality values and learns the nucleotide to nucleotide error rates to determine what types...
  • Learn++

  • Referenced in 8 articles [sw37991]
  • does not forget previously acquired knowledge. Learn++ utilizes ensemble of classifiers by generating multiple hypotheses ... upper bound on the error of the classifiers constructed by Learn++ is also provided...
  • CAD2RL

  • Referenced in 1 article [sw35708]
  • without a Single Real Image, Deep reinforcement learning has emerged as a promising and powerful ... autonomous flight, where a trial-and-error learning process is often impractical. In this paper...
  • FRESH

  • Referenced in 3 articles [sw28344]
  • method based on learning from the errors of our super-resolution result at lower resolution...
  • DeepFix

  • Referenced in 2 articles [sw28854]
  • DeepFix: Fixing Common C Language Errors by Deep Learning. The problem of automatically fixing programming...
  • Reveal

  • Referenced in 21 articles [sw00801]
  • learning” similar in spirit to conflict-based learning in modern Boolean satisfiability solvers. The abstraction/refinement ... correct or an actual design error is reported. The Reveal system allows some user control...
  • Pex

  • Referenced in 35 articles [sw07263]
  • test inputs for Parameterized Unit Tests. Pex learns the program behavior by monitoring execution traces ... extensively tested over several years. Pex found errors, including a serious issue...
  • GSGP

  • Referenced in 4 articles [sw18790]
  • inducing a unimodal error surface for any supervised learning problem, i.e., any problem consisting...
  • OBOE

  • Referenced in 3 articles [sw35832]
  • tasks to enable widespread use of machine learning by non-experts. This paper introduces OBOE ... cross-validated errors of a large number of supervised learning models (algorithms together with hyperparameters ... fits a low rank model to learn the low-dimensional feature vectors for the models ... datasets that best predict the cross-validated errors. To find promising models...