• DeepWalk

  • Referenced in 63 articles [sw39604]
  • online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make...
  • RRIA

  • Referenced in 16 articles [sw02558]
  • incremental knowledge acquisition algorithm. As a special way in which the human brain is learning ... algorithm that can learn new knowledge quickly, based on original knowledge learned before ... rule tree based incremental knowledge acquisition algorithm. It can learn from a domain data ... incrementally. Our simulation results show that our algorithm can learn more quickly than classical rough...
  • Learn++

  • Referenced in 8 articles [sw37991]
  • Learn++: an incremental learning algorithm for supervised neural networks. We introduce Learn++, an algorithm ... algorithm does not require access to previously used data during subsequent incremental learning sessions ... does not forget previously acquired knowledge. Learn++ utilizes ensemble of classifiers by generating multiple hypotheses ... task. Initial results indicate that the proposed algorithm works rather well in practice. A theoretical...
  • RSofia

  • Referenced in 1 article [sw10618]
  • suite of fast incremental algorithms for machine learning that can be used for training models...
  • GAssist

  • Referenced in 7 articles [sw08533]
  • Pittsburgh-style learning classifier system (LCS). It uses a standard genetic algorithm to evolve ... data mining problems: A windowing system Incremental Learning with Alternative Strata (ILAS) to improve...
  • RLLib

  • Referenced in 2 articles [sw14311]
  • library that implements incremental, standard, and gradient temporal-difference learning algorithms in Reinforcement Learning...
  • LBTest

  • Referenced in 1 article [sw40823]
  • makes use of incremental learning and model checking algorithms to automate: i) test case generation...
  • PANFIS

  • Referenced in 9 articles [sw13735]
  • PANFIS: A Novel Incremental Learning Machine. Most of the dynamics in real-world systems ... overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in nonstationary environment entails a system owning ... level. An exposure of a novel algorithm, namely parsimonious network based on fuzzy inference system...
  • ILPME

  • Referenced in 2 articles [sw27486]
  • details: https://arxiv.org/pdf/1802.07966.pdf. Incremental and iterative learning of answer set programs from mutually distinct ... datasets which have given the machine learning algorithms the opportunity to learn various skills across...
  • RLgraph

  • Referenced in 2 articles [sw31155]
  • implement, execute and test due to algorithmic instability, hyper-parameter sensitivity, and heterogeneous distributed communication ... library for designing and executing reinforcement learning tasks in both static graph and define ... paradigms. The resulting implementations are robust, incrementally testable, and yield high performance across different deep...
  • AlphaClean

  • Referenced in 1 article [sw37879]
  • machine learning since the pipeline components and objective functions have structure that tuning algorithms ... pool. Asynchronously, in separate threads, a search algorithm sequences them into cleaning pipelines that maximize ... optimizations including incremental evaluation of the quality measures and learning dynamic pruning rules to reduce...
  • Naiad

  • Referenced in 4 articles [sw32529]
  • ability to perform iterative and incremental computations. Although existing systems offer some of these features ... parallelism across a wide class of algorithms. This model enriches dataflow computation with timestamps that ... streaming data analysis, it- erative machine learning, and interactive graph mining. Naiad outperforms specialized systems...
  • DILS

  • Referenced in 2 articles [sw38269]
  • kind of semi-supervised learning: constrained clustering. This technique is a generalization of traditional clustering ... this paper. We propose a new metaheuristic algorithm, the Dual Iterative Local Search, and prove ... state-of-the-art algorithms on 25 datasets with incremental levels of constraint-based information...
  • OpenLORIS

  • Referenced in 1 article [sw37994]
  • Vision Dataset and Benchmark for Lifelong Deep Learning. The recent breakthroughs in computer vision have ... vision poses unique challenges for applying visual algorithms developed from these standard computer vision datasets ... storage and sometimes privacy issues, while naïve incremental strategies have been shown to suffer from ... with adaptive visual perceptual systems, where lifelong learning is a fundamental capability. However, very...
  • SampleClean

  • Referenced in 1 article [sw37881]
  • namely, materialized view maintenance. To avoid expensive incremental maintenance, we maintain only a sample ... descent algorithm that extends the key ideas to the increasingly common Machine Learning-based analytics...
  • BEAMES

  • Referenced in 1 article [sw41232]
  • Interactive model steering helps people incrementally build machine learning models that are tailored to their ... learning models. The technique steers and samples models from a broader set of learning algorithms...
  • Nieme

  • Referenced in 1 article [sw14441]
  • which unifies several learning algorithms ranging from simple perceptrons to recent models such ... This framework also unifies batch and stochastic learning which are both seen as energy minimization ... scale learning tasks where both the examples and the features are processed incrementally. Being able...
  • EVFDT

  • Referenced in 0 articles [sw23093]
  • EVFDT: An Enhanced Very Fast Decision Tree Algorithm for Detecting Distributed Denial of Service Attack ... such attacks demands an adaptive and incremental learning classifier capable of accurate decision making with ... DDoS attack detection using existing machine learning techniques requires full data set to be stored ... these shortcomings, Very Fast Decision Tree (VFDT) algorithm has been proposed in the past that...
  • CARRADS

  • Referenced in 1 article [sw00106]
  • critical in ad hoc networks. Conventional incremental learning methods are computationally expensive for resource-constrained ... second stage of adaptation is to incrementally update the detection model using the new patterns ... with minimum computational overhead. CARRADS uses SVM algorithm for its superior detection abilities. However, using...
  • Apron

  • Referenced in 69 articles [sw00045]
  • Apron: a library of numerical abstract domains for...