• UCI-ml

  • Referenced in 3266 articles [sw04074]
  • sets as a service to the machine learning community. You may view all data sets ... site is still available, for those who prefer the old format. For a general overview ... site for the Repository. The UCI Machine Learning Repository is a collection of databases, domain...
  • SVMlight

  • Referenced in 263 articles [sw04076]
  • 2002c]. The goal is to learn a function from preference examples, so that it orders...
  • crowdGPPL

  • Referenced in 1 article [sw34403]
  • Scalable Bayesian preference learning for crowds. We propose a scalable Bayesian preference learning method...
  • RAISR

  • Referenced in 3 articles [sw15332]
  • resolution version of it, where the learning is preferably low complexity. In our proposed approach ... processing step to induce the learning of more effective upscaling filters with built-in sharpening...
  • APReL

  • Referenced in 1 article [sw39823]
  • APReL: A Library for Active Preference-based Reward Learning Algorithms. Reward learning is a fundamental ... what their human user wants. Many preference-based learning algorithms and active querying techniques have ... APReL, a library for active preference-based reward learning algorithms, which enable researchers and practitioners...
  • Pareto navigator

  • Referenced in 7 articles [sw31872]
  • multiobjective optimization. We describe a new interactive learning-oriented method called Pareto navigator for nonlinear ... most preferred solution could be located. In this way, the decision maker can learn about...
  • BayesMallows

  • Referenced in 1 article [sw26332]
  • package BayesMallows: Bayesian Preference Learning with the Mallows Rank Model. An implementation of the Bayesian ... model (Vitelli et al., Journal of Machine Learning Research, 2018 ). Both Cayley ... missing rankings, as well as consistent pairwise preferences. Several functions for plotting and studying...
  • L2P

  • Referenced in 2 articles [sw36456]
  • stages. In Stage 1, L2P learns a pairwise preference classifier: is instance A > instance...
  • DeepStyle

  • Referenced in 1 article [sw37572]
  • DeepStyle: Learning User Preferences for Visual Recommendation. Visual information is an important factor in recommender ... styles of items. Style information indicates the preferences of users and has significant effect ... DeepStyle method for learning style features of items and sensing preferences of users. Experiments conducted...
  • ROIAL

  • Referenced in 1 article [sw39824]
  • Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. Characterizing what types ... require recovering a user’s utility landscape. Learning these landscapes is challenging, as walking trajectories ... ensures safety and comfort. ROIAL learns from ordinal and preference feedback, which are more reliable ... inside of a lower-body exoskeleton. ROIAL learns Bayesian posteriors that predict each exoskeleton user...
  • GuideR

  • Referenced in 3 articles [sw30224]
  • GuideR: a guided separate-and-conquer rule learning in classification, regression, and survival settings. This ... introduce user’s preferences or domain knowledge to the rule learning process. Automatic selection...
  • MAMBO

  • Referenced in 1 article [sw07685]
  • broad spectrum of learning strategies and preferences. Parallel to the theoretical presentations, the book includes...
  • SUPERB

  • Referenced in 1 article [sw39134]
  • extracting the representation learned from SSL due to its preferable re-usability. We present...
  • RiPPLE

  • Referenced in 1 article [sw22737]
  • recommends peer learning sessions based on their availability, knowledge state and preferences. This paper describes...
  • Exponentron

  • Referenced in 2 articles [sw26900]
  • preferences or a change of environment. In this paper we present an innovative online learning...
  • ILA-2

  • Referenced in 1 article [sw03301]
  • improved version of a novel Inductive Learning Algorithm (ILA). We first outline the basic algorithm ... preferences through a penalty factor to control the performance of the algorithm. Inductive learning algorithm...
  • TMKink

  • Referenced in 1 article [sw29683]
  • learn how to predict their occurrence. Here, we find that there are local sequence preferences...
  • AET

  • Referenced in 1 article [sw39165]
  • Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data. The success of deep neural ... address this challenge, unsupervised methods are strongly preferred for training neural networks without using ... present a novel paradigm of unsupervised representation learning by Auto-Encoding Transformation (AET) in contrast...
  • GrInvIn

  • Referenced in 8 articles [sw04703]
  • designed to optimally support the user in learning graph theory by means of examples ... find a counterexample to this conjecture (preferably one of smallest possible size...