• TRAMP

  • Referenced in 5 articles [sw08968]
  • Action-model acquisition for planning via transfer learning. Applying learning techniques to acquire action models ... novel algorithm framework, called TRAMP, to learn action models with limited training data ... possible to help the learning task, assuming action models in source domains can be transferred ... weighted formulas. After that it learns action models for the target domain to best explain...
  • OpenCV

  • Referenced in 106 articles [sw11376]
  • computer vision and machine learning algorithms. These algorithms can be used to detect and recognize ... human actions in videos, track camera movements, track moving objects, extract 3D models of objects...
  • R-MAX

  • Referenced in 32 articles [sw02539]
  • very simple model-based reinforcement learning algorithm which can attain near-optimal average reward ... this model. The model is initialized in an optimistic fashion: all actions in all states ... Brafman and Tennenholtz’s LSG algorithm for learning in single controller stochastic games...
  • YACS

  • Referenced in 10 articles [sw04193]
  • actions under some conditions. Accordingly, the latent learning process builds a model of the dynamics...
  • ASMOD

  • Referenced in 14 articles [sw02122]
  • learning paradigm for higher-dimensional data $(>3)$ based on $B$-spline interpolation. The models ... wise model refinement is applied during model training for gradually increasing the modelling capability until ... refinement step a number of possible refinement actions are evaluated, and the one that gives...
  • dagger

  • Referenced in 1 article [sw33466]
  • Recipes). These can include model training, reinitialization, quantization, pruning, learning rate changes, checkpointing, task changes ... other user-defined action that mutates the state of the model or of the experiment...
  • SeqGAN

  • Referenced in 6 articles [sw26534]
  • problems. Modeling the data generator as a stochastic policy in reinforcement learning (RL), SeqGAN bypasses ... passed back to the intermediate state-action steps using Monte Carlo search. Extensive experiments...
  • CNN-RNN

  • Referenced in 8 articles [sw28401]
  • actions and attributes in an image. Traditional approaches to multi-label image classification learn independent ... with CNNs, the proposed CNN-RNN framework learns a joint image-label embedding to characterize ... state-of-the-art multi-label classification model...
  • paper2repo

  • Referenced in 1 article [sw32544]
  • constrained graph convolutional networks (GCN) to automatically learn and map the embeddings of papers ... model training are computed automatically from features of user actions on GitHub. In machine learning...
  • EMP

  • Referenced in 8 articles [sw01086]
  • paper describes a software system that supports model building and numerical solution of various mathematical ... subject to linear or nonlinear constraints. All actions of the system are controlled by menues ... available. The system is capable to learn, i.e. to improve its own knowledge...
  • Holophrasm

  • Referenced in 2 articles [sw30124]
  • Proving in higher order logic using deep learning and eschewing hand-constructed features. Holophrasm exploits ... algorithm and a sequence-to-sequence model for action enumeration. The system proves...
  • SEEC

  • Referenced in 1 article [sw29911]
  • theory and machine learning to reason about previously unseen applications and actions while automatically adapting ... changes in both application and system models. This paper describes the SEEC framework and evaluates ... system. Additional studies show how SEEC can learn optimal resource allocation online and respond...
  • rl-texplore-ros-pkg

  • Referenced in 1 article [sw14315]
  • running reinforcement learning experiments through ROS. Agents and Environments communicate actions, states, and rewards through ... includes a framework for model based agents where various model learning and exploration modules...
  • bandit-nmt

  • Referenced in 1 article [sw20941]
  • generated reference translations. We describe a reinforcement learning algorithm that improves neural machine translation systems ... well-designed for problems with a large action space and delayed rewards, (b) effectively optimizes ... robust to skewed, high-variance, granular feedback modeled after actual human behaviors...
  • SplitBox

  • Referenced in 0 articles [sw15002]
  • providers processing the network functions do not learn the network policies instructing how the functions ... abstract model of a generic network function based on match-action pairs, assuming that this...
  • AENet

  • Referenced in 1 article [sw34921]
  • that our model learnt generic audio features, similar to the way CNNs learn generic features ... leads to significant performance improvements on action recognition and video highlight detection. In video highlight...
  • MultiWOZ

  • Referenced in 1 article [sw36138]
  • Dataset for Task-Oriented Dialogue Modelling. Even though machine learning has become the major scene ... labelled with dialogue belief states and dialogue actions is two-fold: firstly, a detailed description...
  • MADRaS

  • Referenced in 1 article [sw38683]
  • training, inter-vehicular communication, noisy observations, stochastic actions, and custom traffic cars whose behaviors ... particularly suited for curriculum and continual learning. MADRaS is lightweight and it provides a convenient ... MADRaS uses a UDP based client server model where the simulation engine is the server...
  • Facile

  • Referenced in 1 article [sw28767]
  • model. Facile implements the law of mass action to automatically compile a biochemical network (written ... generates the reduced form of a model with the minimum number of independent variables. This ... produces a C version of the reduced model for AUTO. Conclusion: Facile is a simple ... text-based input, Facile is quick to learn and can be incorporated into larger programs...
  • ARMS

  • Referenced in 65 articles [sw00048]
  • ARMS: an algebraic recursive multilevel solver for general...